Content Characteristics and Transmission Strategies of Social Media Rumors in China: Big Data Analysis of WeChat Rumors Understanding the characteristics and patterns of rumors on social media has become one of the key issues of rumor governance. However, there is some empirical evidence about the characteristics of rumors on WeChat, the most popular social media platform in China with more than 800 million users. To investigate the content characteristics and transmission strategies of rumors on WeChat, we collected 2175 rumor articles from WeChat from April 2015 to March 2016. It was found that political and societal rumors accounted for the highest proportion of rumors on WeChat. The proportion of positive emotional words found in the most popular rumors was significantly higher than that in the least popular rumors. Further analysis of rumor transmission strategies indicated that nearly onethird of the rumors have the interactive characteristics of induced sharing. Rumor articles on WeChat were mostly published around peopleu0027s leisure time and holidays. Most articles were published in the front positions at each instance of time. However, the headline rumor articles did not receive the highest number of views and likes. Our findings can be beneficial for the scientific allocation of rumor regulatory resources and rumor intervention.

Prediction and Analysis of Rumours Impact on Social Media Rumour, as an important form of social communication, has been run through the whole evolutionary history of mankind. People maliciously disseminate rumours in order to increase awareness, slander others or cause panic, etc. To eliminate this issue, many researchers resort to detecting rumours on social media. However, rumour detection is not sufficient to eliminate the negative impact, which also requires official institutions to provide the refutations. In practice, the number of rumours on social media is too large, there is no need to refute some rumours with little or no concern. Therefore, we need to evaluate the impact of the rumours in advance. In this paper, we devise a rumour influence prediction model RISM (Rumour Impact on Social Media) based on a popular rumour intensity formula to predict the impact of a newborn rumour. Extensive numerical experiments are carried out on the real rumour data that are collected from Toutiao.com, which demonstrate the effectiveness of our proposed RISM model.