# The Spatial-Temporal Evolution and Influencing Factors of Public Attention to 5G: Empirical Analysis Based on Baidu Index from 2011 to 2021

Authors: Pan Liu; Guanyu Wang; Kai Liu; Junke Li; Yanlin Chen
Journal: Mathematical Problems in Engineering
 (2023)

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## Abstract

The development of 5G (fifth-generation wireless systems) determines the future direction of technology and economy and has received extensive public attention. Studying the changing rules of public attention to 5G can provide an important guiding significance for the sustainable development of 5G. This paper takes Baidu Index as the measurement index of 5G public attention and analyzes the spatial and temporal evolution characteristics and influencing factors of public attention to 5G from 2011 to 2021 by using the elasticity coefficient, Gini coefficient, geographical concentration index, and panel data model. The results of the study show the following. (1) The public concern to 5G is generally on the rise, but the heat has declined in the past two years. (2) The public’s 5G attention shows a seasonal effect, with the highest attention in March and June. (3) The spatial difference of 5G public attention is obvious. The eastern region has a high degree of attention, the internal differences between the eastern and western regions are obvious, and the central region is relatively balanced. (4) The factors such as local economic level, education level, Internet development, and media attention have significantly affected the public focus on 5G. Also, some suggestions are made for the sustainable development of 5G and the planning of 6G (sixth-generation wireless systems).


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## Body

## 1. Introduction

5G began to enter the public eye in 2008 when NASA and M2Mi announced a joint effort to develop 5G technology. China is the leader in 5G technology. From 2013 when Huawei announced that it invested heavily in the research and testing of 5G networks to 2019 when China issued 5G licenses, China’s 5G road was particularly dazzling. Now China has entered the commercial era of 5G.5G determines the future economic development of a country. Whoever grasps 5G may be in a leading position in technological and economic development in the next hundred years [1]. Therefore, 5G has been widely concerned in China. In terms of policy effect, China has ranked first in the number of patent declarations necessary for 5G standards [2]. From an academic point of view, 14900 papers related to 5G were entered into CNKI. In addition, 5G has received a lot of public attention which plays an important role in many fields. Public search behavior can reflect the public’s attitude towards the issue and help the government achieve accurate governance [3]. By analyzing the correlation between mass attention and the number of deaths and infections, Zhou et al. [4] established an early warning and monitoring method for COVID-19 to provide guidance for epidemic prevention and control. In the growth of the enterprise, Ruan and Xiao [5] pointed out that public attention can positively influence the technological innovation of enterprises. In the holding of sports events, Pan and Liu [6] studied the laws and influencing factors of the popular concern about sports, which can help the organizers to do better in the publicity and service of the events. These works inspire us with public care about 5G.


## 2. Related Works

Many scholars have studied the public concern about 5G. For example, Herrera-Contreras et al. [7] counted the public’s emotions and opinions on 5G in the Twitter platform and analyzed the public’s attention data to help technology companies understand the public’s attitude towards 5G technology. Similarly, Ahmed et al. [8] analyzed the COVID-19 conspiracy theory about 5G data released by the public on Twitter and proposed the driving factors and countermeasures of fake news, providing practical guidance for the Health Bureau to combat rumors. Fu et al. [9] investigated the factors affecting the public attitude towards 5G base stations and concluded that the mechanism of public attitude about stations is conducive to the establishment of 5G base stations. Dashtipour et al. [10] paid attention to the public’s attitude towards 5G and tried to change negative emotions into positive ones. Opincariu [11] has argued that public attitudes towards 5G technology are critical to improving the performance of network communications.According to previous studies, the public attention of 5G is valued. However, the public’s research on the regular characteristics of 5G attention is not deep enough. Whether the changes in public attention have regular characteristics is an important research topic. To answer this question, this article studies the characteristics of the temporal and spatial evolution and influencing factors of 5G public attention, providing practical guidance for the government and enterprises to promote and build 5G and the planning of 6G.


## 3. Materials and Methods

The research tool of this paper is Baidu. Baidu scientifically analyzes the search frequency of keywords entered by netizens and obtains Baidu Index. Baidu Index has a great public influence in China, reflecting the overall concern of the domestic public [12]. In order to make the data comprehensive, we counted the sum of PC and mobile search indexes to measure the public attention to the development of 5G.


### 3.1. Research Data

#### 3.1.1. Search Keywords for 5G

We can understand the public concerns through the search results of relevant keywords entered by the public on Baidu. Therefore, it is crucial to mine representative keywords for the research of 5G public attention. In view of this, the steps to search for 5G-related keywords are as follows:(1)
To ensure the directivity of the data, this paper first used “5G” and “5G network” as the benchmark keywords to enter into the Baidu demand graph, then recorded all the keywords in the search relevance intensity area from 2011 to 2021, and finally deleted duplicate keywords to get the initial keywords (see Table1).(2)
Get the search keywords. The primary keywords were searched in Baidu Index one by one, and the keywords that had not been recorded were eliminated. Since some primary keywords interfere with the search of 5G, such as 3G, whose search volume mainly reflects 3G communication and has little relevance to 5G, the search of these keywords will disturb the accuracy of 5G search data, so similar keywords should be removed. Finally, we got the search keywords related to 5G, as shown in Table2. These keywords are input into the website of Baidu Index as combination keywords, and the value of Baidu Index for 5G was obtained, so as to know the changing trend of public attention to 5G.Table 1
Primary keywords of 5G.
1G5G concept5G package5G broadband2GWhen will 5G network become popular5G technologyArtificial intelligence3GWhat is the difference between 5G and 4GInternet of ThingsBig data4GDo you need to change your phone for 5GCloud computingMobile healthcare5G5G leading stocks5G home5G network6G5G mobile phonesSmart lifeMobile technologyTable 2
Search terms for 5G.
5GInternet of ThingsSmart lifeArtificial intelligenceMobile healthcare5G network


#### 3.1.2. Data Source

The public concern about 5G in this paper is obtained by inputting the combined keywords “Internet of Things + 5G + 5G network” and “artificial intelligence + mobile medical + smart life” into the official website of Baidu Index. The study covers the period from 2011 to 2021. The spatial scope of the study includes 31 provinces (autonomous regions and municipalities), excluding Hong Kong, Macao, and Taiwan. The number of netizens comes from the Statistical Report on the Development of the Internet in China released by the China Internet Network Information Center (CNNIC). Indicators such as local economic development level, education level, and Internet development level are all from the National Bureau of Statistics. The media attention index is derived from the Chinese News Database (CND).


### 3.2. Research Methods

To better analyze the spatial-temporal characteristics and influencing factors of public interest in 5G, this paper introduces the elasticity coefficient (k), Gini coefficient (GI), and geographical concentration index (EG).


#### 3.2.1. Elasticity Coefficient

The elasticity coefficient is used to measure the relative change of one variable caused by the change of another variable. Generally speaking, the search volume of 5G-related keywords has a relationship with the number of Internet users. To better determine the evolution of 5G attention, this paper uses the ratio of the growth rate of the 5G Baidu Index and the rate of Internet users as the elasticity coefficient, which is calculated as follows:(1)k=ΔB/BΔI/I,where k denotes the elasticity coefficient, ΔB stands for the amount of change in Baidu Index of 5G, B represents the value of Baidu Index of 5G in the current issue, ΔI denotes the amount of change in Internet users, and I represents the number of online users in the current issue. If k is equal to 1, it means that the public concern on 5G increases simultaneously with the number of Internet users. If k is greater than 1, it means that the public attention to 5G has indeed increased. If k is less than 1, it shows that the increase of people’ concern about 5G may only benefit from the growth of the Internet users rather than the increase of attention itself.


#### 3.2.2. Gini Coefficient

The Gini coefficient is a common index to measure the difference in income distribution among residents in a country and region. In this paper, it is used to reflect the degree of difference in public attention to 5G in different regions. The formula is(2)GI=∑i=1nxi−xmean2/nxmean,where GI denotes the Gini coefficient, xmean denotes the average value of Baidu Index for 5G in the sample regions, xi denotes the value of 5G Baidu Index in a region, and n denotes the number of sample regions. The higher the value of GI, the greater the difference in public attention to 5G.


#### 3.2.3. Geographical Concentration Index

The geographical concentration index is used to measure the concentration degree of the spatial distribution of geographical elements. Some scholars have introduced geographical concentration index to express the attention of “AI + education” [13]. The geographical concentration index in this paper was used to reflect the spatial concentration of the attention to 5G. Its formula is as follows:(3)EG=∑i=1npi2,where EG represents the geographical concentration index, Pi represents the proportion of the 5G Baidu Index value of a region to the total Baidu Index sum, and n represents the number of regions. A large EG indicates that attention for 5G is more concentrated, and vice versa.


## 3.1. Research Data

### 3.1.1. Search Keywords for 5G

We can understand the public concerns through the search results of relevant keywords entered by the public on Baidu. Therefore, it is crucial to mine representative keywords for the research of 5G public attention. In view of this, the steps to search for 5G-related keywords are as follows:(1)
To ensure the directivity of the data, this paper first used “5G” and “5G network” as the benchmark keywords to enter into the Baidu demand graph, then recorded all the keywords in the search relevance intensity area from 2011 to 2021, and finally deleted duplicate keywords to get the initial keywords (see Table1).(2)
Get the search keywords. The primary keywords were searched in Baidu Index one by one, and the keywords that had not been recorded were eliminated. Since some primary keywords interfere with the search of 5G, such as 3G, whose search volume mainly reflects 3G communication and has little relevance to 5G, the search of these keywords will disturb the accuracy of 5G search data, so similar keywords should be removed. Finally, we got the search keywords related to 5G, as shown in Table2. These keywords are input into the website of Baidu Index as combination keywords, and the value of Baidu Index for 5G was obtained, so as to know the changing trend of public attention to 5G.Table 1
Primary keywords of 5G.
1G5G concept5G package5G broadband2GWhen will 5G network become popular5G technologyArtificial intelligence3GWhat is the difference between 5G and 4GInternet of ThingsBig data4GDo you need to change your phone for 5GCloud computingMobile healthcare5G5G leading stocks5G home5G network6G5G mobile phonesSmart lifeMobile technologyTable 2
Search terms for 5G.
5GInternet of ThingsSmart lifeArtificial intelligenceMobile healthcare5G network


### 3.1.2. Data Source

The public concern about 5G in this paper is obtained by inputting the combined keywords “Internet of Things + 5G + 5G network” and “artificial intelligence + mobile medical + smart life” into the official website of Baidu Index. The study covers the period from 2011 to 2021. The spatial scope of the study includes 31 provinces (autonomous regions and municipalities), excluding Hong Kong, Macao, and Taiwan. The number of netizens comes from the Statistical Report on the Development of the Internet in China released by the China Internet Network Information Center (CNNIC). Indicators such as local economic development level, education level, and Internet development level are all from the National Bureau of Statistics. The media attention index is derived from the Chinese News Database (CND).


## 3.1.1. Search Keywords for 5G

We can understand the public concerns through the search results of relevant keywords entered by the public on Baidu. Therefore, it is crucial to mine representative keywords for the research of 5G public attention. In view of this, the steps to search for 5G-related keywords are as follows:(1)
To ensure the directivity of the data, this paper first used “5G” and “5G network” as the benchmark keywords to enter into the Baidu demand graph, then recorded all the keywords in the search relevance intensity area from 2011 to 2021, and finally deleted duplicate keywords to get the initial keywords (see Table1).(2)
Get the search keywords. The primary keywords were searched in Baidu Index one by one, and the keywords that had not been recorded were eliminated. Since some primary keywords interfere with the search of 5G, such as 3G, whose search volume mainly reflects 3G communication and has little relevance to 5G, the search of these keywords will disturb the accuracy of 5G search data, so similar keywords should be removed. Finally, we got the search keywords related to 5G, as shown in Table2. These keywords are input into the website of Baidu Index as combination keywords, and the value of Baidu Index for 5G was obtained, so as to know the changing trend of public attention to 5G.Table 1
Primary keywords of 5G.
1G5G concept5G package5G broadband2GWhen will 5G network become popular5G technologyArtificial intelligence3GWhat is the difference between 5G and 4GInternet of ThingsBig data4GDo you need to change your phone for 5GCloud computingMobile healthcare5G5G leading stocks5G home5G network6G5G mobile phonesSmart lifeMobile technologyTable 2
Search terms for 5G.
5GInternet of ThingsSmart lifeArtificial intelligenceMobile healthcare5G network


## 3.1.2. Data Source

The public concern about 5G in this paper is obtained by inputting the combined keywords “Internet of Things + 5G + 5G network” and “artificial intelligence + mobile medical + smart life” into the official website of Baidu Index. The study covers the period from 2011 to 2021. The spatial scope of the study includes 31 provinces (autonomous regions and municipalities), excluding Hong Kong, Macao, and Taiwan. The number of netizens comes from the Statistical Report on the Development of the Internet in China released by the China Internet Network Information Center (CNNIC). Indicators such as local economic development level, education level, and Internet development level are all from the National Bureau of Statistics. The media attention index is derived from the Chinese News Database (CND).


## 3.2. Research Methods

To better analyze the spatial-temporal characteristics and influencing factors of public interest in 5G, this paper introduces the elasticity coefficient (k), Gini coefficient (GI), and geographical concentration index (EG).


### 3.2.1. Elasticity Coefficient

The elasticity coefficient is used to measure the relative change of one variable caused by the change of another variable. Generally speaking, the search volume of 5G-related keywords has a relationship with the number of Internet users. To better determine the evolution of 5G attention, this paper uses the ratio of the growth rate of the 5G Baidu Index and the rate of Internet users as the elasticity coefficient, which is calculated as follows:(1)k=ΔB/BΔI/I,where k denotes the elasticity coefficient, ΔB stands for the amount of change in Baidu Index of 5G, B represents the value of Baidu Index of 5G in the current issue, ΔI denotes the amount of change in Internet users, and I represents the number of online users in the current issue. If k is equal to 1, it means that the public concern on 5G increases simultaneously with the number of Internet users. If k is greater than 1, it means that the public attention to 5G has indeed increased. If k is less than 1, it shows that the increase of people’ concern about 5G may only benefit from the growth of the Internet users rather than the increase of attention itself.


### 3.2.2. Gini Coefficient

The Gini coefficient is a common index to measure the difference in income distribution among residents in a country and region. In this paper, it is used to reflect the degree of difference in public attention to 5G in different regions. The formula is(2)GI=∑i=1nxi−xmean2/nxmean,where GI denotes the Gini coefficient, xmean denotes the average value of Baidu Index for 5G in the sample regions, xi denotes the value of 5G Baidu Index in a region, and n denotes the number of sample regions. The higher the value of GI, the greater the difference in public attention to 5G.


### 3.2.3. Geographical Concentration Index

The geographical concentration index is used to measure the concentration degree of the spatial distribution of geographical elements. Some scholars have introduced geographical concentration index to express the attention of “AI + education” [13]. The geographical concentration index in this paper was used to reflect the spatial concentration of the attention to 5G. Its formula is as follows:(3)EG=∑i=1npi2,where EG represents the geographical concentration index, Pi represents the proportion of the 5G Baidu Index value of a region to the total Baidu Index sum, and n represents the number of regions. A large EG indicates that attention for 5G is more concentrated, and vice versa.


## 3.2.1. Elasticity Coefficient

The elasticity coefficient is used to measure the relative change of one variable caused by the change of another variable. Generally speaking, the search volume of 5G-related keywords has a relationship with the number of Internet users. To better determine the evolution of 5G attention, this paper uses the ratio of the growth rate of the 5G Baidu Index and the rate of Internet users as the elasticity coefficient, which is calculated as follows:(1)k=ΔB/BΔI/I,where k denotes the elasticity coefficient, ΔB stands for the amount of change in Baidu Index of 5G, B represents the value of Baidu Index of 5G in the current issue, ΔI denotes the amount of change in Internet users, and I represents the number of online users in the current issue. If k is equal to 1, it means that the public concern on 5G increases simultaneously with the number of Internet users. If k is greater than 1, it means that the public attention to 5G has indeed increased. If k is less than 1, it shows that the increase of people’ concern about 5G may only benefit from the growth of the Internet users rather than the increase of attention itself.


## 3.2.2. Gini Coefficient

The Gini coefficient is a common index to measure the difference in income distribution among residents in a country and region. In this paper, it is used to reflect the degree of difference in public attention to 5G in different regions. The formula is(2)GI=∑i=1nxi−xmean2/nxmean,where GI denotes the Gini coefficient, xmean denotes the average value of Baidu Index for 5G in the sample regions, xi denotes the value of 5G Baidu Index in a region, and n denotes the number of sample regions. The higher the value of GI, the greater the difference in public attention to 5G.


## 3.2.3. Geographical Concentration Index

The geographical concentration index is used to measure the concentration degree of the spatial distribution of geographical elements. Some scholars have introduced geographical concentration index to express the attention of “AI + education” [13]. The geographical concentration index in this paper was used to reflect the spatial concentration of the attention to 5G. Its formula is as follows:(3)EG=∑i=1npi2,where EG represents the geographical concentration index, Pi represents the proportion of the 5G Baidu Index value of a region to the total Baidu Index sum, and n represents the number of regions. A large EG indicates that attention for 5G is more concentrated, and vice versa.


## 4. Results and Analysis

### 4.1. Temporal Characteristics of Public Attention to 5G

As the core of the information industrial revolution and the key factor of artificial intelligence, 5G has attracted wide attention at home and abroad. In China, the public is taking 5G especially seriously. This paper analyzes the annual and monthly differences in public concern about 5G.


#### 4.1.1. Annual Difference of Public Attention to 5G

Figure1 takes Internet of Things + 5G + 5G network and artificial intelligence + mobile medical + smart life as combination keywords and calculates the change trend of national 5G attention from 2011 to 2021.Figure 1
The trend of public attention to 5G from 2011 to 2021.From Figure1, we can know the following information:(1)
From 2011 to 2019, public attention to 5G shows an increasing trend, indicating the rapid development of 5G technology. Especially from 2016 to 2019, the increase of Baidu Index is high, and the reason for this phenomenon is that in 2016, the Ministry of Industry and Information Technology officially launched the 5G technology research and development test, which means that the development of 5G has entered the development stage. In 2019, the commercial promotion of 5G was officially launched.(2)
In the past two years, the attention of 5G has shown a downward trend, which may be due to the following reasons. (1) 5G’s development has shifted from the construction stage to the application service stage, the number of relevant policies issued has decreased, and public attention has decreased accordingly [14]. (2) The high cost of 5G applications, the large number of base stations needed to be built, and the lack of application scenarios have led to the fact that 5G has not brought us a better life experience at present, so the public attention to 5G has decreased.As we all know, the change in Baidu Index is closely related to the trend of Internet users. To better reflect the change in public attention, this paper introduces the elastic coefficient. Figure2 shows the changing trend of the elastic coefficient of 5G attention in China.Figure 2
Trends in the elasticity coefficients of public attention to 5G from 2011 to 2021.From Figure2, we obtained the following information:(1)
The 5G attention shows a fluctuating trend. From 2011 to 2019, the elasticity coefficients are greater than 1, showing the rising trend of attention heat, which is closely related to the development of 5G.(2)
After 2018, the elasticity coefficient of 5G decreases year by year, but the elasticity coefficients in 2018 and 2019 are greater than 1, showing that the rate of 5G attention slows down in 2018 and 2019.(3)
After 2020, the value of elasticity coefficient is negative, meaning that the rate of 5G attention has been smaller than rate of the number of Internet users, meaning that the public attention of 5G shows a decreasing trend.As can be seen from Figures1 and 2,(1)
There were two peaks in the elasticity coefficients in 2014 and 2017, which may be attributed to the following reasons. (1) In 2014, the National 863 Program launched a major project to implement 5G advance research, which received widespread attention in China. (2) In 2017, the world’s first commercially deployable 5G standard, 5GNR, was released, and China played a central role in the development of the standard, which caused quite a stir in the country.(2)
In 2020 and 2021, the attention of 5G and the elasticity coefficient show a decreasing trend, which may be related to the shift of the attention group of 5G from the whole population to professional researchers in recent years. Deng [15] has pointed out that the influence of policies and media will increase public attention, and when the fever subsides, public attention will gradually decrease. Meanwhile, in China, the 5G application scenario is in the exploration stage of heavy industry and has not yet penetrated into our daily life [16].


#### 4.1.2. Monthly Differences in 5G Public Attention

To obtain the monthly changes of 5G attention in a year, we recorded the 5G Baidu Index values from January to December for a total of 11 years from 2011 to 2021, as shown in Figure3.Figure 3
Trend of 5G public attention from January to December.From Figure3, we can see the following:(1)
The monthly trend of 5G attention is consistent from 2011 to 2021. In 2019, 5G attention is the highest, while in 2011, the attention is the lowest, which is closely related to the development of 5G.(2)
Monthly concerns show a cyclical change; with March, June, and September as the dividing line, we find a consistent trend of change in concerns from January to March, April to June, July to September, and October to December.(3)
There were two peaks in attention, in March and June. However, the troughs of 5G attention were in January and December. This suggests that governments and companies should avoid the beginning and end of the year when promulgating 5G-related policies and making announcements about 5G-related products, with March and June being the preferred months.


### 4.2. Spatial Characteristics of Public Attention to 5G

This paper analyzes the spatial evolution trend and spatial geographical concentration for public attention to 5G.


#### 4.2.1. Spatial Evolution Trend of Public Attention to 5G

In this paper, the Baidu Index values of 5G in 31 provinces from 2011 to 2021 are counted, and they are averaged to obtain the overall situation of 5G concern, as shown in Figure4. Meanwhile, we analyze the changes of 5G concern between provinces, as shown in Figure 5.Figure 4
Mean value distribution of 5G concerns between 2011 and 2021.Figure 5
Trend of 5G public attention among 31 provinces and cities from 2011 to 2021.As can be seen from Figure4, 5G public attention is unevenly distributed among the 31 provinces, with Guangdong, Beijing, Jiangsu, Shanghai, and Zhejiang among the provinces and cities with high 5G attention. Provinces with low 5G attention include Tibet, Qinghai, Ningxia, Hainan, and Guizhou, and provinces with intermediate attention include Sichuan, Henan, and Hubei.On the website of Baidu Index, 5G combination keyword was used as the search term, the region was limited to provinces, and the time period was 2011 to 2021; then, the values of the Baidu Index of 31 provinces were obtained (see Figure5).From Figure5, it can be seen that(1)
The trend of 5G concern is consistent among provinces. The change of attention is on a straight line and is on a steadily decreasing trend. From 2013 to 2019, the level of concern increases linearly. In 2020 and 2021, the level of concern shows a decreasing trend. This is in line with the overall national trend (see Figure1). From this, we can see that in the future, when we study the relevant public attention trends, we can choose a few representative provinces and cities and do not need to study all of them.(2)
For each year from 2011 to 2021, the attention of Guangdong, Beijing, Jiangsu, and Zhejiang provinces has been higher, while the attention of Tibet, Qinghai, Ningxia, and Hainan provinces has been lower. Guangdong Province, in particular, is far ahead of other provinces in terms of 5G attention. Combined with Figure4, we can see that the provinces with high public attention are not only shown in the mean value, but also in the unit attention.In order to understand the change of 5G public attention in Eastern China, Central China, and Western China, we counted the trend of 5G Baidu Index averages in the three regions, as shown in Figure6.Figure 6
Trends in the mean value of 5G public attention in the three major regions from 2011 to 2021.From Figure6, we can get the following information:(1)
5G concern in the three major regions shows a trend of rising and then falling. From 2011 to 2019, it has been on an upward trend, and in 2020, the attention starts to decline. This trend is in line with Figures1 and 5.(2)
Between 2011 and 2021, 5G attention is highest in the eastern region and lowest in the western region. The population size and economic development level may be influencing factors, with the population in the east generally being larger than that in the central and western regions. 5G is a high-tech industry, and the investment in 5G technology in economically developed regions is unmatched by other less developed provinces.


#### 4.2.2. Spatial Distribution of 5G Attention

In this paper, we use the geographical concentration index to measure the spatial geographical clustering of 5G public attention in the country and the Gini coefficient to evaluate the degree of spatial non-equilibrium of 5G attention between provinces and within the three major regions of east, central, and west (see Table3).Table 3
Geographic concentration index and Gini coefficient of public interest in 5G from 2011 to 2021.
YearGeographic concentration indexInter-provincial differencesRegional differencesEastCentralWest20110.20600.56150.41270.22430.486820120.20460.54530.39530.22130.494020130.20090.50140.36480.21160.488520140.19960.48480.35140.19760.484620150.20140.50770.37660.21110.519920160.20360.53330.41290.20150.558820170.20920.59750.47870.23130.507920180.22930.60230.47910.26420.490420190.20890.59410.46880.25960.511320200.20260.52170.42150.21800.481920210.19850.47110.38230.22410.4305From Table3, it can be seen that(1)
From the geographical concentration index, the values are low, meaning that the concentration of public care to 5G is not high, relatively scattered, and not concentrated in some specific provinces and cities, reflecting that 5G has received general attention nationwide.(2)
From the inter-provincial Gini coefficient, the value decreases from 0.5615 in 2011 to 0.4848 in 2014 and then rises again, demonstrating the low attention to 5G and small differences among provinces before 2014. From 2014 to 2019, 5G began to develop rapidly, and the differences in attention among provinces became larger. Recently, the amount of information on 5G has become more available in each region through various channels, and the difference in public attention is gradually narrowing.(3)
From the intra-regional Gini coefficient, the unbalanced degree of public attention to 5G is higher in the eastern and western regions. The central region is relatively more balanced. In terms of the trend of change, the differences in the eastern and central regions show a decreasing-rising-decreasing trend, suggesting that there is a phase trend in the degree of non-equilibrium within the east and central regions. However, the differences in the western region display a rising-declining trend, reflecting that the degree of internal disequilibrium in the western region still has a tendency to diminish.(4)
It is worth noting that the geographical concentration index, the degree of inter-provincial non-equilibrium, and the degree of non-equilibrium in eastern and western regions all shrink in 2021 compared with 2020 and do not continue the previous upward trend, which indicates that there is a likely trend of concentration of public attention on 5G among provinces, especially in eastern and western regions.


### 4.3. Influencing Factors of Public Attention to 5G

#### 4.3.1. Analysis of Influencing Factors

It has been shown that public attention is influenced by local economic level, education level, Internet development, and media attention [17, 18]. Therefore, this paper argues that these factors still affect 5G public attention. We selected the GDP per capita to measure the local economic level, the number of higher education graduates to indicate the education level, the number of Internet broadband access ports to indicate the Internet development, and the number of news reports about 5G in the CND to be used as the media attention indicator. The influencing factors and related indicators are shown in Table 4.Table 4
Influencing factors of public attention to 5G.
Influencing factorIndicatorUnitLocal economic levelGDP per capitaYuanEducation levelHigher education graduates104 peopleInternet developmentNumber of broadband Internet access ports104 piecesMedia attentionNews reports in CNDPiece(1) Local Economic Level. The preliminary analysis of this paper shows that the provinces with high public attention to 5G are Beijing, Guangdong, Jiangsu, Zhejiang, and Shanghai (see Figures 4 and 5), which indicates that the people’s care to 5G is related to the local economic level. In this paper, local economic level is measured by local GDP per capita.(2) Education Level. Higher education promotes the development of high-tech industries [19]. 5G, as a representative of highly sophisticated technology, may be influenced by higher education. In this paper, we used the number of higher education graduates to represent the education level.(3) Internet Development. In the information age, the tool to achieve public attention is the Internet. Generally speaking, with the development of the Internet, the possibility of the public searching for 5G through the Internet becomes greater. Liu et al. [17] argues that Internet informatization affects public attention. In this paper, the number of Internet broadband access ports is used to measure the level of Internet development.(4) Media Attention. Neuman’s empirical study confirmed that public attention is influenced by news coverage [20]. Media attention has been measured using the number of relevant news reports [21, 22]. As shown in Table 4, the number of news reports on 5G is also an important influencing factor for public attention to 5G, which is consistent with the findings of McCombs and Shaw’s empirical study [23]. In this paper, two mainstream media, traditional media and online media, were selected in each province and city, and the selected media are shown in Table 5. These media were used as 5G news sources in each province and city, and 5G-related keywords were entered into the CND to retrieve the amount of 5G news coverage in each province. In this paper, the amount of news reports for 5G is used as the media attention indicator.Table 5
Local media studied in this paper.
ProvinceMediaProvinceMediaBeijingBeijing Daily, BJD NewsHunanHunan Daily, Hunan OnlineTianjinTianjin Daily, Tianjin People’s Radio NetworkHubeiHubei Daily, Jingchu NetworkHebeiHebei Daily, Hebei News NetworkHenanHenan Daily, Dahe NetworkShanxiShanxi Daily, Shanxi Network Radio and Television NetworkGuangxiGuangxi Daily, Guangxi News NetworkInner MongoliaInner Mongolia Daily, North News NetworkHainanHainan Daily, HinewsLiaoningLiaoning Daily, Beiguo NetworkSichuanSichuan Daily, Sichuan News NetworkJilinJilin Daily, China Jilin NetworkChongqingChongqing Daily, CqnewsHeilongjiangHeilongjiang Daily, Heilongjiang News NetworkYunnanYunnan Daily, Yunnan NetworkShanghaiJiefang Daily, EastdayGuizhouGuizhou Daily, Colorful Guizhou NetworkJiangsuXinhua Daily, Xinhua News NetworkShaanxiShaanxi Daily, Shaanxi Media NetworkZhejiangZhejiang Daily, Zhejiang OnlineGansuGansu Daily, Qinghai News NetworkAnhuiAnhui Daily, Zhongan OnlineQinghaiQinghai Daily, Qinghai News NetworkFujianFujian Daily, Minnan NetworkTibetTibet Daily, China Tibet News NetworkJiangxiJiangxi Daily, Jiangxi News NetworkXinjiangXinjiang Daily, Xinjiang News OnlineShandongDazhong Daily, Dazhong NetworkNingxiaNingxia Daily, Ningxia News NetworkGuangdongNanfang Daily, South Network


#### 4.3.2. Model Construction of Influencing Factors

To verify the specific inference of the above factors on public attention of 5G, the following model is selected:(4)lnyit=b+λ1lnx1it+λ2lnx2it+λ3lnx3it+λ4lnx4it+δit,where yit represents the Baidu Index value of province i in year t, x1it ∼ x4it denote the per capita GDP of province i in year t, the number of college graduates, the number of Internet broadband access, and the number of news reports, λ1∼λ4 represent the influence coefficient of each factor, b denotes the constant term, and δit represents the random disturbance term. In order to eliminate heteroscedasticity and reduce the error caused by data dimensional inconsistency, natural logarithms are taken for all variables.


#### 4.3.3. Model Results

In this paper, data on 5G attention and influencing factors in 31 provinces of China from 2011 to 2021 were calculated. The optimal model was determined by borrowing the Hausman test in Stata16.0 software. Subsequently, the influencing factors of 5G attention in the country and the eastern, central, and western regions were tested, comparing thep value between fixed effect model and random effect model, and if the p value was less than 0.05, the fixed effect model was selected, and vice versa. After statistical analysis, we got the results (see Table 6).Table 6
Regression results of the influencing factors model.
Variable31 provincesEasternMiddleWesternb−5.466∗∗∗ (−4.09)−5.344∗∗∗ (−4.53)−4.375∗∗∗ (−3.38)−2.699∗ (−2.29)lnx10.737∗∗∗ (4.35)0.685∗∗∗ (5.66)0.455∗∗ (3.20)0.324∗ (2.44)lnx2−0.675∗∗∗ (−4.65)−0.259∗ (−2.04)−0.258∗∗ (−2.99)−0.182∗∗ (−2.66)lnx30.0441∗∗ (3.03)0.0849∗∗∗ (3.86)0.0072 (0.26)0.0327 (1.95)lnx40.778∗∗∗ (11.47)0.633∗∗∗ (6.36)0.923∗∗∗ (8.96)0.825∗∗∗ (10.72)Model typeFixed effectRandom effectRandom effectRandom effectThe values in parentheses indicate statistical values.∗, ∗∗, and ∗∗∗ indicate significance at 1%, 5%, and 10% levels, respectively.From Table6, it can be seen that(1)
Among the national regions, GDP per capita, the number of graduates from higher education, media attention, and the number of Internet network broadband access ports all significantly influence the public concern of 5G. Furthermore, the effect of the number of Internet broadband ports is large, showing the largest influence on the attention of 5G. The GDP per capita, media attention, and the number of Internet broadband access ports all positively contribute to the public attention of 5G. However, the number of general higher education graduates showed a significant inverse relationship, which is inconsistent with our common sense. Possible reasons are as follows: first, the number of people who graduated from higher education schools is statistically more inclined to use new online media such as microblogs and microvideos to follow 5G information [24]; second, the number of people who graduated from higher education schools is statistically insignificantly changed, and the uncounted secondary school graduates’ attention to 5G may have influenced the results.(2)
Among the three major regions, the four factors have different degrees of influence on the east, central, and west regions. GDP per capita, the amount of news coverage, and the number of Internet broadband access ports all have a positive effect on 5G attention in the east, with GDP per capita having the largest effect, which is consistent with our earlier analysis that provinces with high level in economy have a high attention to 5G. In the central and western regions, both GDP per capita and the number of Internet broadband access ports promote public attention to 5G, while the amount of news coverage does not have a significant effect on the attention to 5G probably because the main news content of these local media is in the areas of government, transportation, health, and meteorology, resulting in limited user engagement in 5G in local media alone.


## 4.1. Temporal Characteristics of Public Attention to 5G

As the core of the information industrial revolution and the key factor of artificial intelligence, 5G has attracted wide attention at home and abroad. In China, the public is taking 5G especially seriously. This paper analyzes the annual and monthly differences in public concern about 5G.


### 4.1.1. Annual Difference of Public Attention to 5G

Figure1 takes Internet of Things + 5G + 5G network and artificial intelligence + mobile medical + smart life as combination keywords and calculates the change trend of national 5G attention from 2011 to 2021.Figure 1
The trend of public attention to 5G from 2011 to 2021.From Figure1, we can know the following information:(1)
From 2011 to 2019, public attention to 5G shows an increasing trend, indicating the rapid development of 5G technology. Especially from 2016 to 2019, the increase of Baidu Index is high, and the reason for this phenomenon is that in 2016, the Ministry of Industry and Information Technology officially launched the 5G technology research and development test, which means that the development of 5G has entered the development stage. In 2019, the commercial promotion of 5G was officially launched.(2)
In the past two years, the attention of 5G has shown a downward trend, which may be due to the following reasons. (1) 5G’s development has shifted from the construction stage to the application service stage, the number of relevant policies issued has decreased, and public attention has decreased accordingly [14]. (2) The high cost of 5G applications, the large number of base stations needed to be built, and the lack of application scenarios have led to the fact that 5G has not brought us a better life experience at present, so the public attention to 5G has decreased.As we all know, the change in Baidu Index is closely related to the trend of Internet users. To better reflect the change in public attention, this paper introduces the elastic coefficient. Figure2 shows the changing trend of the elastic coefficient of 5G attention in China.Figure 2
Trends in the elasticity coefficients of public attention to 5G from 2011 to 2021.From Figure2, we obtained the following information:(1)
The 5G attention shows a fluctuating trend. From 2011 to 2019, the elasticity coefficients are greater than 1, showing the rising trend of attention heat, which is closely related to the development of 5G.(2)
After 2018, the elasticity coefficient of 5G decreases year by year, but the elasticity coefficients in 2018 and 2019 are greater than 1, showing that the rate of 5G attention slows down in 2018 and 2019.(3)
After 2020, the value of elasticity coefficient is negative, meaning that the rate of 5G attention has been smaller than rate of the number of Internet users, meaning that the public attention of 5G shows a decreasing trend.As can be seen from Figures1 and 2,(1)
There were two peaks in the elasticity coefficients in 2014 and 2017, which may be attributed to the following reasons. (1) In 2014, the National 863 Program launched a major project to implement 5G advance research, which received widespread attention in China. (2) In 2017, the world’s first commercially deployable 5G standard, 5GNR, was released, and China played a central role in the development of the standard, which caused quite a stir in the country.(2)
In 2020 and 2021, the attention of 5G and the elasticity coefficient show a decreasing trend, which may be related to the shift of the attention group of 5G from the whole population to professional researchers in recent years. Deng [15] has pointed out that the influence of policies and media will increase public attention, and when the fever subsides, public attention will gradually decrease. Meanwhile, in China, the 5G application scenario is in the exploration stage of heavy industry and has not yet penetrated into our daily life [16].


### 4.1.2. Monthly Differences in 5G Public Attention

To obtain the monthly changes of 5G attention in a year, we recorded the 5G Baidu Index values from January to December for a total of 11 years from 2011 to 2021, as shown in Figure3.Figure 3
Trend of 5G public attention from January to December.From Figure3, we can see the following:(1)
The monthly trend of 5G attention is consistent from 2011 to 2021. In 2019, 5G attention is the highest, while in 2011, the attention is the lowest, which is closely related to the development of 5G.(2)
Monthly concerns show a cyclical change; with March, June, and September as the dividing line, we find a consistent trend of change in concerns from January to March, April to June, July to September, and October to December.(3)
There were two peaks in attention, in March and June. However, the troughs of 5G attention were in January and December. This suggests that governments and companies should avoid the beginning and end of the year when promulgating 5G-related policies and making announcements about 5G-related products, with March and June being the preferred months.


## 4.1.1. Annual Difference of Public Attention to 5G

Figure1 takes Internet of Things + 5G + 5G network and artificial intelligence + mobile medical + smart life as combination keywords and calculates the change trend of national 5G attention from 2011 to 2021.Figure 1
The trend of public attention to 5G from 2011 to 2021.From Figure1, we can know the following information:(1)
From 2011 to 2019, public attention to 5G shows an increasing trend, indicating the rapid development of 5G technology. Especially from 2016 to 2019, the increase of Baidu Index is high, and the reason for this phenomenon is that in 2016, the Ministry of Industry and Information Technology officially launched the 5G technology research and development test, which means that the development of 5G has entered the development stage. In 2019, the commercial promotion of 5G was officially launched.(2)
In the past two years, the attention of 5G has shown a downward trend, which may be due to the following reasons. (1) 5G’s development has shifted from the construction stage to the application service stage, the number of relevant policies issued has decreased, and public attention has decreased accordingly [14]. (2) The high cost of 5G applications, the large number of base stations needed to be built, and the lack of application scenarios have led to the fact that 5G has not brought us a better life experience at present, so the public attention to 5G has decreased.As we all know, the change in Baidu Index is closely related to the trend of Internet users. To better reflect the change in public attention, this paper introduces the elastic coefficient. Figure2 shows the changing trend of the elastic coefficient of 5G attention in China.Figure 2
Trends in the elasticity coefficients of public attention to 5G from 2011 to 2021.From Figure2, we obtained the following information:(1)
The 5G attention shows a fluctuating trend. From 2011 to 2019, the elasticity coefficients are greater than 1, showing the rising trend of attention heat, which is closely related to the development of 5G.(2)
After 2018, the elasticity coefficient of 5G decreases year by year, but the elasticity coefficients in 2018 and 2019 are greater than 1, showing that the rate of 5G attention slows down in 2018 and 2019.(3)
After 2020, the value of elasticity coefficient is negative, meaning that the rate of 5G attention has been smaller than rate of the number of Internet users, meaning that the public attention of 5G shows a decreasing trend.As can be seen from Figures1 and 2,(1)
There were two peaks in the elasticity coefficients in 2014 and 2017, which may be attributed to the following reasons. (1) In 2014, the National 863 Program launched a major project to implement 5G advance research, which received widespread attention in China. (2) In 2017, the world’s first commercially deployable 5G standard, 5GNR, was released, and China played a central role in the development of the standard, which caused quite a stir in the country.(2)
In 2020 and 2021, the attention of 5G and the elasticity coefficient show a decreasing trend, which may be related to the shift of the attention group of 5G from the whole population to professional researchers in recent years. Deng [15] has pointed out that the influence of policies and media will increase public attention, and when the fever subsides, public attention will gradually decrease. Meanwhile, in China, the 5G application scenario is in the exploration stage of heavy industry and has not yet penetrated into our daily life [16].


## 4.1.2. Monthly Differences in 5G Public Attention

To obtain the monthly changes of 5G attention in a year, we recorded the 5G Baidu Index values from January to December for a total of 11 years from 2011 to 2021, as shown in Figure3.Figure 3
Trend of 5G public attention from January to December.From Figure3, we can see the following:(1)
The monthly trend of 5G attention is consistent from 2011 to 2021. In 2019, 5G attention is the highest, while in 2011, the attention is the lowest, which is closely related to the development of 5G.(2)
Monthly concerns show a cyclical change; with March, June, and September as the dividing line, we find a consistent trend of change in concerns from January to March, April to June, July to September, and October to December.(3)
There were two peaks in attention, in March and June. However, the troughs of 5G attention were in January and December. This suggests that governments and companies should avoid the beginning and end of the year when promulgating 5G-related policies and making announcements about 5G-related products, with March and June being the preferred months.


## 4.2. Spatial Characteristics of Public Attention to 5G

This paper analyzes the spatial evolution trend and spatial geographical concentration for public attention to 5G.


### 4.2.1. Spatial Evolution Trend of Public Attention to 5G

In this paper, the Baidu Index values of 5G in 31 provinces from 2011 to 2021 are counted, and they are averaged to obtain the overall situation of 5G concern, as shown in Figure4. Meanwhile, we analyze the changes of 5G concern between provinces, as shown in Figure 5.Figure 4
Mean value distribution of 5G concerns between 2011 and 2021.Figure 5
Trend of 5G public attention among 31 provinces and cities from 2011 to 2021.As can be seen from Figure4, 5G public attention is unevenly distributed among the 31 provinces, with Guangdong, Beijing, Jiangsu, Shanghai, and Zhejiang among the provinces and cities with high 5G attention. Provinces with low 5G attention include Tibet, Qinghai, Ningxia, Hainan, and Guizhou, and provinces with intermediate attention include Sichuan, Henan, and Hubei.On the website of Baidu Index, 5G combination keyword was used as the search term, the region was limited to provinces, and the time period was 2011 to 2021; then, the values of the Baidu Index of 31 provinces were obtained (see Figure5).From Figure5, it can be seen that(1)
The trend of 5G concern is consistent among provinces. The change of attention is on a straight line and is on a steadily decreasing trend. From 2013 to 2019, the level of concern increases linearly. In 2020 and 2021, the level of concern shows a decreasing trend. This is in line with the overall national trend (see Figure1). From this, we can see that in the future, when we study the relevant public attention trends, we can choose a few representative provinces and cities and do not need to study all of them.(2)
For each year from 2011 to 2021, the attention of Guangdong, Beijing, Jiangsu, and Zhejiang provinces has been higher, while the attention of Tibet, Qinghai, Ningxia, and Hainan provinces has been lower. Guangdong Province, in particular, is far ahead of other provinces in terms of 5G attention. Combined with Figure4, we can see that the provinces with high public attention are not only shown in the mean value, but also in the unit attention.In order to understand the change of 5G public attention in Eastern China, Central China, and Western China, we counted the trend of 5G Baidu Index averages in the three regions, as shown in Figure6.Figure 6
Trends in the mean value of 5G public attention in the three major regions from 2011 to 2021.From Figure6, we can get the following information:(1)
5G concern in the three major regions shows a trend of rising and then falling. From 2011 to 2019, it has been on an upward trend, and in 2020, the attention starts to decline. This trend is in line with Figures1 and 5.(2)
Between 2011 and 2021, 5G attention is highest in the eastern region and lowest in the western region. The population size and economic development level may be influencing factors, with the population in the east generally being larger than that in the central and western regions. 5G is a high-tech industry, and the investment in 5G technology in economically developed regions is unmatched by other less developed provinces.


### 4.2.2. Spatial Distribution of 5G Attention

In this paper, we use the geographical concentration index to measure the spatial geographical clustering of 5G public attention in the country and the Gini coefficient to evaluate the degree of spatial non-equilibrium of 5G attention between provinces and within the three major regions of east, central, and west (see Table3).Table 3
Geographic concentration index and Gini coefficient of public interest in 5G from 2011 to 2021.
YearGeographic concentration indexInter-provincial differencesRegional differencesEastCentralWest20110.20600.56150.41270.22430.486820120.20460.54530.39530.22130.494020130.20090.50140.36480.21160.488520140.19960.48480.35140.19760.484620150.20140.50770.37660.21110.519920160.20360.53330.41290.20150.558820170.20920.59750.47870.23130.507920180.22930.60230.47910.26420.490420190.20890.59410.46880.25960.511320200.20260.52170.42150.21800.481920210.19850.47110.38230.22410.4305From Table3, it can be seen that(1)
From the geographical concentration index, the values are low, meaning that the concentration of public care to 5G is not high, relatively scattered, and not concentrated in some specific provinces and cities, reflecting that 5G has received general attention nationwide.(2)
From the inter-provincial Gini coefficient, the value decreases from 0.5615 in 2011 to 0.4848 in 2014 and then rises again, demonstrating the low attention to 5G and small differences among provinces before 2014. From 2014 to 2019, 5G began to develop rapidly, and the differences in attention among provinces became larger. Recently, the amount of information on 5G has become more available in each region through various channels, and the difference in public attention is gradually narrowing.(3)
From the intra-regional Gini coefficient, the unbalanced degree of public attention to 5G is higher in the eastern and western regions. The central region is relatively more balanced. In terms of the trend of change, the differences in the eastern and central regions show a decreasing-rising-decreasing trend, suggesting that there is a phase trend in the degree of non-equilibrium within the east and central regions. However, the differences in the western region display a rising-declining trend, reflecting that the degree of internal disequilibrium in the western region still has a tendency to diminish.(4)
It is worth noting that the geographical concentration index, the degree of inter-provincial non-equilibrium, and the degree of non-equilibrium in eastern and western regions all shrink in 2021 compared with 2020 and do not continue the previous upward trend, which indicates that there is a likely trend of concentration of public attention on 5G among provinces, especially in eastern and western regions.


## 4.2.1. Spatial Evolution Trend of Public Attention to 5G

In this paper, the Baidu Index values of 5G in 31 provinces from 2011 to 2021 are counted, and they are averaged to obtain the overall situation of 5G concern, as shown in Figure4. Meanwhile, we analyze the changes of 5G concern between provinces, as shown in Figure 5.Figure 4
Mean value distribution of 5G concerns between 2011 and 2021.Figure 5
Trend of 5G public attention among 31 provinces and cities from 2011 to 2021.As can be seen from Figure4, 5G public attention is unevenly distributed among the 31 provinces, with Guangdong, Beijing, Jiangsu, Shanghai, and Zhejiang among the provinces and cities with high 5G attention. Provinces with low 5G attention include Tibet, Qinghai, Ningxia, Hainan, and Guizhou, and provinces with intermediate attention include Sichuan, Henan, and Hubei.On the website of Baidu Index, 5G combination keyword was used as the search term, the region was limited to provinces, and the time period was 2011 to 2021; then, the values of the Baidu Index of 31 provinces were obtained (see Figure5).From Figure5, it can be seen that(1)
The trend of 5G concern is consistent among provinces. The change of attention is on a straight line and is on a steadily decreasing trend. From 2013 to 2019, the level of concern increases linearly. In 2020 and 2021, the level of concern shows a decreasing trend. This is in line with the overall national trend (see Figure1). From this, we can see that in the future, when we study the relevant public attention trends, we can choose a few representative provinces and cities and do not need to study all of them.(2)
For each year from 2011 to 2021, the attention of Guangdong, Beijing, Jiangsu, and Zhejiang provinces has been higher, while the attention of Tibet, Qinghai, Ningxia, and Hainan provinces has been lower. Guangdong Province, in particular, is far ahead of other provinces in terms of 5G attention. Combined with Figure4, we can see that the provinces with high public attention are not only shown in the mean value, but also in the unit attention.In order to understand the change of 5G public attention in Eastern China, Central China, and Western China, we counted the trend of 5G Baidu Index averages in the three regions, as shown in Figure6.Figure 6
Trends in the mean value of 5G public attention in the three major regions from 2011 to 2021.From Figure6, we can get the following information:(1)
5G concern in the three major regions shows a trend of rising and then falling. From 2011 to 2019, it has been on an upward trend, and in 2020, the attention starts to decline. This trend is in line with Figures1 and 5.(2)
Between 2011 and 2021, 5G attention is highest in the eastern region and lowest in the western region. The population size and economic development level may be influencing factors, with the population in the east generally being larger than that in the central and western regions. 5G is a high-tech industry, and the investment in 5G technology in economically developed regions is unmatched by other less developed provinces.


## 4.2.2. Spatial Distribution of 5G Attention

In this paper, we use the geographical concentration index to measure the spatial geographical clustering of 5G public attention in the country and the Gini coefficient to evaluate the degree of spatial non-equilibrium of 5G attention between provinces and within the three major regions of east, central, and west (see Table3).Table 3
Geographic concentration index and Gini coefficient of public interest in 5G from 2011 to 2021.
YearGeographic concentration indexInter-provincial differencesRegional differencesEastCentralWest20110.20600.56150.41270.22430.486820120.20460.54530.39530.22130.494020130.20090.50140.36480.21160.488520140.19960.48480.35140.19760.484620150.20140.50770.37660.21110.519920160.20360.53330.41290.20150.558820170.20920.59750.47870.23130.507920180.22930.60230.47910.26420.490420190.20890.59410.46880.25960.511320200.20260.52170.42150.21800.481920210.19850.47110.38230.22410.4305From Table3, it can be seen that(1)
From the geographical concentration index, the values are low, meaning that the concentration of public care to 5G is not high, relatively scattered, and not concentrated in some specific provinces and cities, reflecting that 5G has received general attention nationwide.(2)
From the inter-provincial Gini coefficient, the value decreases from 0.5615 in 2011 to 0.4848 in 2014 and then rises again, demonstrating the low attention to 5G and small differences among provinces before 2014. From 2014 to 2019, 5G began to develop rapidly, and the differences in attention among provinces became larger. Recently, the amount of information on 5G has become more available in each region through various channels, and the difference in public attention is gradually narrowing.(3)
From the intra-regional Gini coefficient, the unbalanced degree of public attention to 5G is higher in the eastern and western regions. The central region is relatively more balanced. In terms of the trend of change, the differences in the eastern and central regions show a decreasing-rising-decreasing trend, suggesting that there is a phase trend in the degree of non-equilibrium within the east and central regions. However, the differences in the western region display a rising-declining trend, reflecting that the degree of internal disequilibrium in the western region still has a tendency to diminish.(4)
It is worth noting that the geographical concentration index, the degree of inter-provincial non-equilibrium, and the degree of non-equilibrium in eastern and western regions all shrink in 2021 compared with 2020 and do not continue the previous upward trend, which indicates that there is a likely trend of concentration of public attention on 5G among provinces, especially in eastern and western regions.


## 4.3. Influencing Factors of Public Attention to 5G

### 4.3.1. Analysis of Influencing Factors

It has been shown that public attention is influenced by local economic level, education level, Internet development, and media attention [17, 18]. Therefore, this paper argues that these factors still affect 5G public attention. We selected the GDP per capita to measure the local economic level, the number of higher education graduates to indicate the education level, the number of Internet broadband access ports to indicate the Internet development, and the number of news reports about 5G in the CND to be used as the media attention indicator. The influencing factors and related indicators are shown in Table 4.Table 4
Influencing factors of public attention to 5G.
Influencing factorIndicatorUnitLocal economic levelGDP per capitaYuanEducation levelHigher education graduates104 peopleInternet developmentNumber of broadband Internet access ports104 piecesMedia attentionNews reports in CNDPiece(1) Local Economic Level. The preliminary analysis of this paper shows that the provinces with high public attention to 5G are Beijing, Guangdong, Jiangsu, Zhejiang, and Shanghai (see Figures 4 and 5), which indicates that the people’s care to 5G is related to the local economic level. In this paper, local economic level is measured by local GDP per capita.(2) Education Level. Higher education promotes the development of high-tech industries [19]. 5G, as a representative of highly sophisticated technology, may be influenced by higher education. In this paper, we used the number of higher education graduates to represent the education level.(3) Internet Development. In the information age, the tool to achieve public attention is the Internet. Generally speaking, with the development of the Internet, the possibility of the public searching for 5G through the Internet becomes greater. Liu et al. [17] argues that Internet informatization affects public attention. In this paper, the number of Internet broadband access ports is used to measure the level of Internet development.(4) Media Attention. Neuman’s empirical study confirmed that public attention is influenced by news coverage [20]. Media attention has been measured using the number of relevant news reports [21, 22]. As shown in Table 4, the number of news reports on 5G is also an important influencing factor for public attention to 5G, which is consistent with the findings of McCombs and Shaw’s empirical study [23]. In this paper, two mainstream media, traditional media and online media, were selected in each province and city, and the selected media are shown in Table 5. These media were used as 5G news sources in each province and city, and 5G-related keywords were entered into the CND to retrieve the amount of 5G news coverage in each province. In this paper, the amount of news reports for 5G is used as the media attention indicator.Table 5
Local media studied in this paper.
ProvinceMediaProvinceMediaBeijingBeijing Daily, BJD NewsHunanHunan Daily, Hunan OnlineTianjinTianjin Daily, Tianjin People’s Radio NetworkHubeiHubei Daily, Jingchu NetworkHebeiHebei Daily, Hebei News NetworkHenanHenan Daily, Dahe NetworkShanxiShanxi Daily, Shanxi Network Radio and Television NetworkGuangxiGuangxi Daily, Guangxi News NetworkInner MongoliaInner Mongolia Daily, North News NetworkHainanHainan Daily, HinewsLiaoningLiaoning Daily, Beiguo NetworkSichuanSichuan Daily, Sichuan News NetworkJilinJilin Daily, China Jilin NetworkChongqingChongqing Daily, CqnewsHeilongjiangHeilongjiang Daily, Heilongjiang News NetworkYunnanYunnan Daily, Yunnan NetworkShanghaiJiefang Daily, EastdayGuizhouGuizhou Daily, Colorful Guizhou NetworkJiangsuXinhua Daily, Xinhua News NetworkShaanxiShaanxi Daily, Shaanxi Media NetworkZhejiangZhejiang Daily, Zhejiang OnlineGansuGansu Daily, Qinghai News NetworkAnhuiAnhui Daily, Zhongan OnlineQinghaiQinghai Daily, Qinghai News NetworkFujianFujian Daily, Minnan NetworkTibetTibet Daily, China Tibet News NetworkJiangxiJiangxi Daily, Jiangxi News NetworkXinjiangXinjiang Daily, Xinjiang News OnlineShandongDazhong Daily, Dazhong NetworkNingxiaNingxia Daily, Ningxia News NetworkGuangdongNanfang Daily, South Network


### 4.3.2. Model Construction of Influencing Factors

To verify the specific inference of the above factors on public attention of 5G, the following model is selected:(4)lnyit=b+λ1lnx1it+λ2lnx2it+λ3lnx3it+λ4lnx4it+δit,where yit represents the Baidu Index value of province i in year t, x1it ∼ x4it denote the per capita GDP of province i in year t, the number of college graduates, the number of Internet broadband access, and the number of news reports, λ1∼λ4 represent the influence coefficient of each factor, b denotes the constant term, and δit represents the random disturbance term. In order to eliminate heteroscedasticity and reduce the error caused by data dimensional inconsistency, natural logarithms are taken for all variables.


### 4.3.3. Model Results

In this paper, data on 5G attention and influencing factors in 31 provinces of China from 2011 to 2021 were calculated. The optimal model was determined by borrowing the Hausman test in Stata16.0 software. Subsequently, the influencing factors of 5G attention in the country and the eastern, central, and western regions were tested, comparing thep value between fixed effect model and random effect model, and if the p value was less than 0.05, the fixed effect model was selected, and vice versa. After statistical analysis, we got the results (see Table 6).Table 6
Regression results of the influencing factors model.
Variable31 provincesEasternMiddleWesternb−5.466∗∗∗ (−4.09)−5.344∗∗∗ (−4.53)−4.375∗∗∗ (−3.38)−2.699∗ (−2.29)lnx10.737∗∗∗ (4.35)0.685∗∗∗ (5.66)0.455∗∗ (3.20)0.324∗ (2.44)lnx2−0.675∗∗∗ (−4.65)−0.259∗ (−2.04)−0.258∗∗ (−2.99)−0.182∗∗ (−2.66)lnx30.0441∗∗ (3.03)0.0849∗∗∗ (3.86)0.0072 (0.26)0.0327 (1.95)lnx40.778∗∗∗ (11.47)0.633∗∗∗ (6.36)0.923∗∗∗ (8.96)0.825∗∗∗ (10.72)Model typeFixed effectRandom effectRandom effectRandom effectThe values in parentheses indicate statistical values.∗, ∗∗, and ∗∗∗ indicate significance at 1%, 5%, and 10% levels, respectively.From Table6, it can be seen that(1)
Among the national regions, GDP per capita, the number of graduates from higher education, media attention, and the number of Internet network broadband access ports all significantly influence the public concern of 5G. Furthermore, the effect of the number of Internet broadband ports is large, showing the largest influence on the attention of 5G. The GDP per capita, media attention, and the number of Internet broadband access ports all positively contribute to the public attention of 5G. However, the number of general higher education graduates showed a significant inverse relationship, which is inconsistent with our common sense. Possible reasons are as follows: first, the number of people who graduated from higher education schools is statistically more inclined to use new online media such as microblogs and microvideos to follow 5G information [24]; second, the number of people who graduated from higher education schools is statistically insignificantly changed, and the uncounted secondary school graduates’ attention to 5G may have influenced the results.(2)
Among the three major regions, the four factors have different degrees of influence on the east, central, and west regions. GDP per capita, the amount of news coverage, and the number of Internet broadband access ports all have a positive effect on 5G attention in the east, with GDP per capita having the largest effect, which is consistent with our earlier analysis that provinces with high level in economy have a high attention to 5G. In the central and western regions, both GDP per capita and the number of Internet broadband access ports promote public attention to 5G, while the amount of news coverage does not have a significant effect on the attention to 5G probably because the main news content of these local media is in the areas of government, transportation, health, and meteorology, resulting in limited user engagement in 5G in local media alone.


## 4.3.1. Analysis of Influencing Factors

It has been shown that public attention is influenced by local economic level, education level, Internet development, and media attention [17, 18]. Therefore, this paper argues that these factors still affect 5G public attention. We selected the GDP per capita to measure the local economic level, the number of higher education graduates to indicate the education level, the number of Internet broadband access ports to indicate the Internet development, and the number of news reports about 5G in the CND to be used as the media attention indicator. The influencing factors and related indicators are shown in Table 4.Table 4
Influencing factors of public attention to 5G.
Influencing factorIndicatorUnitLocal economic levelGDP per capitaYuanEducation levelHigher education graduates104 peopleInternet developmentNumber of broadband Internet access ports104 piecesMedia attentionNews reports in CNDPiece(1) Local Economic Level. The preliminary analysis of this paper shows that the provinces with high public attention to 5G are Beijing, Guangdong, Jiangsu, Zhejiang, and Shanghai (see Figures 4 and 5), which indicates that the people’s care to 5G is related to the local economic level. In this paper, local economic level is measured by local GDP per capita.(2) Education Level. Higher education promotes the development of high-tech industries [19]. 5G, as a representative of highly sophisticated technology, may be influenced by higher education. In this paper, we used the number of higher education graduates to represent the education level.(3) Internet Development. In the information age, the tool to achieve public attention is the Internet. Generally speaking, with the development of the Internet, the possibility of the public searching for 5G through the Internet becomes greater. Liu et al. [17] argues that Internet informatization affects public attention. In this paper, the number of Internet broadband access ports is used to measure the level of Internet development.(4) Media Attention. Neuman’s empirical study confirmed that public attention is influenced by news coverage [20]. Media attention has been measured using the number of relevant news reports [21, 22]. As shown in Table 4, the number of news reports on 5G is also an important influencing factor for public attention to 5G, which is consistent with the findings of McCombs and Shaw’s empirical study [23]. In this paper, two mainstream media, traditional media and online media, were selected in each province and city, and the selected media are shown in Table 5. These media were used as 5G news sources in each province and city, and 5G-related keywords were entered into the CND to retrieve the amount of 5G news coverage in each province. In this paper, the amount of news reports for 5G is used as the media attention indicator.Table 5
Local media studied in this paper.
ProvinceMediaProvinceMediaBeijingBeijing Daily, BJD NewsHunanHunan Daily, Hunan OnlineTianjinTianjin Daily, Tianjin People’s Radio NetworkHubeiHubei Daily, Jingchu NetworkHebeiHebei Daily, Hebei News NetworkHenanHenan Daily, Dahe NetworkShanxiShanxi Daily, Shanxi Network Radio and Television NetworkGuangxiGuangxi Daily, Guangxi News NetworkInner MongoliaInner Mongolia Daily, North News NetworkHainanHainan Daily, HinewsLiaoningLiaoning Daily, Beiguo NetworkSichuanSichuan Daily, Sichuan News NetworkJilinJilin Daily, China Jilin NetworkChongqingChongqing Daily, CqnewsHeilongjiangHeilongjiang Daily, Heilongjiang News NetworkYunnanYunnan Daily, Yunnan NetworkShanghaiJiefang Daily, EastdayGuizhouGuizhou Daily, Colorful Guizhou NetworkJiangsuXinhua Daily, Xinhua News NetworkShaanxiShaanxi Daily, Shaanxi Media NetworkZhejiangZhejiang Daily, Zhejiang OnlineGansuGansu Daily, Qinghai News NetworkAnhuiAnhui Daily, Zhongan OnlineQinghaiQinghai Daily, Qinghai News NetworkFujianFujian Daily, Minnan NetworkTibetTibet Daily, China Tibet News NetworkJiangxiJiangxi Daily, Jiangxi News NetworkXinjiangXinjiang Daily, Xinjiang News OnlineShandongDazhong Daily, Dazhong NetworkNingxiaNingxia Daily, Ningxia News NetworkGuangdongNanfang Daily, South Network


## 4.3.2. Model Construction of Influencing Factors

To verify the specific inference of the above factors on public attention of 5G, the following model is selected:(4)lnyit=b+λ1lnx1it+λ2lnx2it+λ3lnx3it+λ4lnx4it+δit,where yit represents the Baidu Index value of province i in year t, x1it ∼ x4it denote the per capita GDP of province i in year t, the number of college graduates, the number of Internet broadband access, and the number of news reports, λ1∼λ4 represent the influence coefficient of each factor, b denotes the constant term, and δit represents the random disturbance term. In order to eliminate heteroscedasticity and reduce the error caused by data dimensional inconsistency, natural logarithms are taken for all variables.


## 4.3.3. Model Results

In this paper, data on 5G attention and influencing factors in 31 provinces of China from 2011 to 2021 were calculated. The optimal model was determined by borrowing the Hausman test in Stata16.0 software. Subsequently, the influencing factors of 5G attention in the country and the eastern, central, and western regions were tested, comparing thep value between fixed effect model and random effect model, and if the p value was less than 0.05, the fixed effect model was selected, and vice versa. After statistical analysis, we got the results (see Table 6).Table 6
Regression results of the influencing factors model.
Variable31 provincesEasternMiddleWesternb−5.466∗∗∗ (−4.09)−5.344∗∗∗ (−4.53)−4.375∗∗∗ (−3.38)−2.699∗ (−2.29)lnx10.737∗∗∗ (4.35)0.685∗∗∗ (5.66)0.455∗∗ (3.20)0.324∗ (2.44)lnx2−0.675∗∗∗ (−4.65)−0.259∗ (−2.04)−0.258∗∗ (−2.99)−0.182∗∗ (−2.66)lnx30.0441∗∗ (3.03)0.0849∗∗∗ (3.86)0.0072 (0.26)0.0327 (1.95)lnx40.778∗∗∗ (11.47)0.633∗∗∗ (6.36)0.923∗∗∗ (8.96)0.825∗∗∗ (10.72)Model typeFixed effectRandom effectRandom effectRandom effectThe values in parentheses indicate statistical values.∗, ∗∗, and ∗∗∗ indicate significance at 1%, 5%, and 10% levels, respectively.From Table6, it can be seen that(1)
Among the national regions, GDP per capita, the number of graduates from higher education, media attention, and the number of Internet network broadband access ports all significantly influence the public concern of 5G. Furthermore, the effect of the number of Internet broadband ports is large, showing the largest influence on the attention of 5G. The GDP per capita, media attention, and the number of Internet broadband access ports all positively contribute to the public attention of 5G. However, the number of general higher education graduates showed a significant inverse relationship, which is inconsistent with our common sense. Possible reasons are as follows: first, the number of people who graduated from higher education schools is statistically more inclined to use new online media such as microblogs and microvideos to follow 5G information [24]; second, the number of people who graduated from higher education schools is statistically insignificantly changed, and the uncounted secondary school graduates’ attention to 5G may have influenced the results.(2)
Among the three major regions, the four factors have different degrees of influence on the east, central, and west regions. GDP per capita, the amount of news coverage, and the number of Internet broadband access ports all have a positive effect on 5G attention in the east, with GDP per capita having the largest effect, which is consistent with our earlier analysis that provinces with high level in economy have a high attention to 5G. In the central and western regions, both GDP per capita and the number of Internet broadband access ports promote public attention to 5G, while the amount of news coverage does not have a significant effect on the attention to 5G probably because the main news content of these local media is in the areas of government, transportation, health, and meteorology, resulting in limited user engagement in 5G in local media alone.


## 5. Conclusions

This paper studies the spatial and temporal evolution trends and influencing factors of 5G public attention from 2011 to 2021 in 31 provinces of China based on Baidu Index. The main findings of this paper are shown below.(1)
The temporal characteristics of 5G attention in China are obvious. Specifically, with the advance of time, 5G public attention shows an upward trend, but in the last two years, it began to decline. Public attention to 5G shows a seasonal effect, with the highest attention in March and June and the lowest attention in January and February.(2)
The spatial characteristics of 5G public attention in China are obvious. The provinces with high 5G attention are Guangdong, Beijing, Jiangsu, Shanghai, and Zhejiang. Similarly, among the three major regions, 5G public attention is highest in the east and lowest in the west. The differences in 5G attention nationwide have been decreasing in recent years, with the unevenness of public attention to 5G being higher in the eastern and western regions and relatively more balanced in the central region. The non-equilibrium degree of 5G public attention in the west tends to weaken, while the trend in the east and central regions is not obvious.(3)
Local economic level, education level, Internet development, and media attention all influenced public attention to 5G. Except for the number of higher education graduates, all other factors positively influenced 5G attention, and the factor of the number of Internet broadband access ports had the greatest effect. Also, all four factors influenced public concern about 5G in the eastern region, while the amount of news did not have a significant effect on 5G attention in the central and western regions.


## 6. Discussion

In this paper, we examine the public interest in 5G to inform about the continued development of 5G as well as 6G, and we make the following recommendations.(1)
Focus on the time evolution trend of 5G attention: Its change can reflect the influence of 5G in the whole society. Understanding its trend can help governments and enterprises grasp the current status and the future of 5G and make targeted decisions.(2)
Strengthen the development and promotion of 5G application scenarios: The attention to 5G has declined in the last two years, probably because the level and quality of 5G application services are lower than our expectations, but we must recognize that the growth of 5G requires a longer process. To achieve the goal of 5G’s immersive services, we must focus on the development and promotion of 5G application scenarios.(3)
Reasonable choice of 5G promotion time: according to the monthly characteristics of 5G attention, March and June have the highest attention, which suggests that the government and enterprises can set the time of 5G policy release and product marketing and promotion to March and June, which can maximize the popularity of 5G and better promote the development of 5G.(4)
Early planning for 6G: 6G should be planned with reference to the characteristics of the temporal and spatial patterns of public attention for 5G. For example, the government should strengthen 6G publicity in the central and western regions at an early stage and raise attention for 6G by influencing related factors.This paper gives the regular characteristics of 5G public attention and puts forward some suggestions for 5G development. However, limited by the availability of data, we only consider the Baidu Index, which cannot fully portray the public attention on 5G. Based on this, subsequent studies should include relevant indexes of other platforms, for example, WeChat index and Weibo index. Moreover, the information mining of annual and monthly differences in this paper is not thorough, so advanced methods should be used to fully obtain the information [25, 26]. In addition, media attention, a influencing factors of 5G attention, is only measured by selecting two mainstream media in each province, which is not comprehensive enough. Future research should comprehensively analyze all mainstream media to better reflect the influence of media attention on 5G public attention.



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*Source: 1187545-2023-02-18.xml*