# A Network Analysis Approach to Detecting Social Issues with Web-Based Data
## 5 Concluding Remarks  
This study aimed to address the ongoing task of detecting and resolving social issues by proposing a quantitative approach based on web-based data. It focused on identifying the time period when social issues emerged and determining the most urgent issues that require immediate attention. By constructing keyword co-occurrence networks usingvalid keywords extracted from web-based data, this study monitored our society by calculating the structural changes in the networks over time to identify the specific time period when social issues occurred. Subsequently, social issue candidates were defined, and their priorities were derived based on their impact on the network's structural changes. As a result, this study detected urgent social issues that our society should pay attention to and respond to first. This study has major contributions in two aspects. First, from an academic perspective, this study contributes by proposing a new approach to detecting social issues based on the definition and characteristics of an issue, unlike previous studies that mainly focus on the frequency of certain topics to detect issues. Specifically, the proposed approach constructed keyword co-occurrence networks to represent various stories in our society. Next, the structural changes of the networks were monitored using the network structure entropy to capture moments when members of the society are focused on specific topics. As a result, the proposed approach quantitatively provides the time when social issues occurred by identifying the time period when the structure of the network changes rapidly. An issue is a topic that suddenly becomes of interest to people. Thus, the approach proposed in this study can suggest when social issues occurred by identifying when members of society focus on certain topics, which is a new issue detection approach based on the definition and characteristics of an issue. Next, from a practical perspective, the proposed approach offers valuable support for timely responses to social issues by quantitatively measuring and suggesting their occurrence time period and priority. The prioritization of social issue candidates was not solely based on frequency, but rather on their impact score, which quantifies their influence on structural changes in the network. Candidates with a high impact score have contributed significantly to structural changes in the network, indicating their impact. With limited resources available to address the numerous social issues across various fields such as culture, economy, industry, and technology, it is crucial to efficiently address them in a sequential manner. The proposed approach can support decision-making for organizations, including governments and corporations, by providing priorities for social issue candidates at the time period when social issues occurred. This enables the efficient allocation of resources to address urgent social issues. Moreover, the approach can assist the establishment of future-oriented responses to social issues by providing insights into their developmental directions, as discussed in Section 4.2 of this study. Despite the contributions, there are several areas for future research to consider. Firstly, although the study proposed a social issue detection approach using quantitative methods, it did not suggest a method for verifying the results of this study using quantitative indicators. Instead, based on the qualitative judgment of the authors, it is judged that the social issues that were of great social concern in South Korea at the time, including the DEF issue, were adequately detected. Future research should focus on conducting quantitative verification of the identified time periods and detected social issues. Moreover, it will be possible to compare issue detection performance with other studies through quantitative verification. Secondly, this study primarily focused on web news data from South Korea. To assess the usefulness of the proposed approach, conducting case studies in other countries is necessary.