ABSTRACT
COVID-19 has dramatically changed the social situation in Japan. Along with the change in the real society, COVID-19 also changes the usage of social media. This study reports on findings from an analysis of onomatopoeia appears in posts on social media regarding COVID-19 to see how it has affected people's emotion. We analyzed the frequency of appearance of onomatopoeias expressing specific emotions according to the time variation, the relation between major events such as the declaration of state of emergency, and changes of co-occurrence words for the onomatopoeias. As a result of analysis, we found that the frequencies and degree of variation of onomatopoeias that belong to the same emotion group are complexly associated. The analysis results on co-occurrence words and frequency shift by events suggest that the cause of the change in emotion was different even for the onomatopoeia expressing the same emotion. The long-term emotional changes marked the peak in June 2020 during the second COVID-19 outbreak in Japan, rather than the first outbreak occurred in April 2020. At this time, as the number of infected people increased, the frequency of the use of the onomatopoeias also tended to increase. From the first case of COVID-19 in Japan (Jan 2019) to the second outbreak (Jun 2020), "anger "and "fear"were dominant emotions then they change to "peace of mind"during the second peak to the third outbreak (Nov 2020), and finally become "disgust". © 2021 ACM.
ABSTRACT
This study focuses on how scientifically-correct information is disseminated through social media, and how misinformation can be corrected. We have identified examples on Twitter where scientific terms that have been misused have been rectified and replaced by scientifically-correct terms through the interaction of users. The results show that the percentage of correct terms ("variant (åCurrency sign‰ç•°æ "or "COVID-19 variant (åCurrency sign‰ç•°ã▪ãCurrency signã«ã)") being used instead of the incorrect terms ("strain (åCurrency sign‰ç•°ç®)") on Twitter has already increased since the end of December 2020. This was about a month before the release of an official statement by the Japanese Association for Infectious Diseases regarding the correct terminology, and the use of terms on social media was faster than it was in television. Some Twitter users who quickly started using the correct term were more likely to retweet messages sent by leading influencers on Twitter, rather than messages sent by traditional media or portal sites. However, a few Twitter users continued to use wrong terms even after March 2021, even though the use of the correct terms was widespread. Further analysis of their tweets revealed that they were quoting sources that differed from that of other users. This study empirically verified that self-correction occurs even on Twitter, which is often known as a "hotbed for spreading rumors."The results of this study also suggest that influencers with expertise can influence the direction of public opinion on social media and that the media that users usually cite can also affect the possibility of behavioral changes. © 2021 ACM.
ABSTRACT
The e-commerce market, which has attracted much attention in recent years, has been growing rapidly since the COVID-19 pandemic. Among these, the growth of the market for consumer-to-consumer(C2C) transactions has been remarkable. However, few studies have analyzed the C2C market during the COVID-19 pandemic, and in particular, the behavioral tendencies of the sellers are not well understood. In this study, we used C2C market transaction data to analyze the behavior of users who joined the C2C platform during the COVID-19 pandemic and identified the users who continued to use it. We found that a large number of users registered for the service to trade face masks that were in short supply in the market due to heavy demand. In addition, among the users who traded masks, only the sellers continued to use the service at a high rate, suggesting that the successful experience of selling masks is important for seller retention. These results will provide useful insights to design and implement concrete strategies for seller retention. © 2021 IEEE.
ABSTRACT
For efficient policy-making, a thorough recognition of controversial topics is crucial because the cost of unmitigated controversies would be extremely high for society. However, identifying controversial topics is costly. In this paper, we proposed a framework to search for controversial topics comprehensively. We then conducted a retrospective analysis of the controversial topics of COVID-19 with data obtained via Twitter in Japan as a case study of the framework. The results show that the proposed framework can effectively detect controversial topics that reflect current reality. Controversial topics tend to be about the government, medical matters, economy, and education;moreover, the controversy score had a low correlation with the traditional indicators-scale and sentiment of the topics-which suggests that the controversy score is a potentially important indicator to be obtained. We also discussed the difference between highly controversial topics and less controversial ones despite their large scale and sentiment. © 2021 ACM.
ABSTRACT
Using a new opinion dynamics using the polarity analysis of measured data of Twitter about "toilet paper" and "COVID-19", we analyzed the chain of fear that people feel for the rumor of lack of toilet paper and COVID-19 itself. We use opinion dynamics for the analysis of the fears, and we obtain the opinion distribution of the fear calculated using the opinion dynamics and the observed distribution. By comparing the two distribution, we found that the opinion distribution for the fear is consisted with the mixture of trust and distrust.