Do Emotions Determine Rumors and Impact the Financial Market? The Case of Demonetization in India Studies have identified that rumors circulate in social media and rumors influence different areas of decisionmaking. Given that rumors are essentially psychological phenomena, there are not enough studies that explore how textual contentbased emotions determine social media rumors. Further, while behavioral finance identifies rumors as influencing financial markets, the relationship between social media rumors and financial markets is not well studied. This paper attempts to provide a direction for understanding these two questions. In the context of demonetization in India it finds that while textbased emotion extraction helps identify rumors circulating on social media, these emotions do not impact the movement of the financial market.

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.