An Exploratory Study of COVID-19 Misinformation on Twitter

During the COVID-19 pandemic, social media has become a home ground for misinformation. To tackle this infodemic, scientific oversight, as well as a better understanding by practitioners in crisis management, is needed. We have conducted an exploratory study into the propagation, authors and content of misinformation on Twitter around the topic of COVID-19 in order to gain early insights. We have collected all tweets mentioned in the verdicts of fact-checked claims related to COVID-19 by over 92 professional fact-checking organisations between January and mid-July 2020 and share this corpus with the community. This resulted in 1 500 tweets relating to 1 274 false and 276 partially false claims, respectively. Exploratory analysis of author accounts revealed that the verified twitter handle(including Organisation/celebrity) are also involved in either creating (new tweets) or spreading (retweet) the misinformation. Additionally, we found that false claims propagate faster than partially false claims. Compare to a background corpus of COVID-19 tweets, tweets with misinformation are more often concerned with discrediting other information on social media. Authors use less tentative language and appear to be more driven by concerns of potential harm to others. Our results enable us to suggest gaps in the current scientific coverage of the topic as well as propose actions for authorities and social media users to counter misinformation.Comment: 20 pages, nine figures, four tables. Submitted for peer review, revision

Sentiment Analysis Of Web Forums: Comparison Between SentiWordNet And SentiStrength

Internet has become a major tool for communication, training, fundraising, media operations, and recruitment, and these processes often use web forums. This paper intended to find suitable technique for analysing selected web forums that included radical content by presenting a comparison between SentiWordNet and SentiStrength. SentiWordNet is a lexical resource for supporting opinion mining by assigning a positivity score and a negativity score to each WordNet. SentiStrength is a technique that was developed from comments on MySpace. It uses human-designed lexical and emotional terms with a set of amplification, diminishing and negation rules. The results have been presented and discussed

Sentiment cascades in the 15M movement

Recent grassroots movements have suggested that online social networks might play a key role in their organization, as adherents have a fast, many-to-many, communication channel to help coordinate their mobilization. The structure and dynamics of the networks constructed from the digital traces of protesters have been analyzed to some extent recently. However, less effort has been devoted to the analysis of the semantic content of messages exchanged during the protest. Using the data obtained from a microblogging service during the brewing and active phases of the 15M movement in Spain, we perform the first large scale test of theories on collective emotions and social interaction in collective actions. Our findings show that activity and information cascades in the movement are larger in the presence of negative collective emotions and when users express themselves in terms related to social content. At the level of individual participants, our results show that their social integration in the movement, as measured through social network metrics, increases with their level of engagement and of expression of negativity. Our findings show that non-rational factors play a role in the formation and activity of social movements through online media, having important consequences for viral spreading.Comment: EPJ Data Science vol 4 (2015) (forthcoming

Sentiment analysis during Hurricane Sandy in emergency response

Sentiment analysis has been widely researched in the domain of online review sites with the aim of generating summarized opinions of users about different aspects of products. However, there has been little work focusing on identifying the polarity of sentiments expressed by users during disaster events. Identifying such sentiments from online social networking sites can help emergency responders understand the dynamics of the network, e.g., the main users' concerns, panics, and the emotional impacts of interactions among members. In this paper, we perform a sentiment analysis of tweets posted on Twitter during the disastrous Hurricane Sandy and visualize online users' sentiments on a geographical map centered around the hurricane. We show how users' sentiments change according not only to their locations, but also based on the distance from the disaster. In addition, we study how the divergence of sentiments in a tweet posted during the hurricane affects the tweet retweetability. We find that extracting sentiments during a disaster may help emergency responders develop stronger situational awareness of the disaster zone itself

Hubungan Kematangan Emosi dengan Kecenderungan Perilaku Cyberbullying pada Pengguna Twitter di Universitas Sarjanawiyata Tamansiswa YOGYAKARTA

This research aims to determine the relationship between emotional maturity and tendencies of cyberbullying behavior on twitter user. The hypothesis, there is a negative relationship between emotional maturity and cyberbullying behavior tendencies on twitter user. The subjects are students at the University Sarjanawiyata Tamansiswa Under graduated program, 18-24 years old, male and female, and have a twitter account, amounting to 82 people. The measures used tendencies of cyberbullying behavior scale and emotional maturity scale. Data processed using the Product Moment of Pearson technique with the help of statistical program SPSS version 20 for Mac. The results of relationship values obtained relationship between emotional maturity and tendencies of cyberbullying behavior of (r)= -0283 with p = 0.005 (p < 0.05). This shows that the hypothesis shows there is a negative relationship between emotional maturity and tendencies of cyberbullying behavior are acceptable. It means that the higher the emotional maturity of students twitter users then the lower the tendencies of cyberbullying behavior. Conversely the lower the emotional maturity of twitter users, the higher the tendencies of cyberbullying behavior

Crisis Communication on Twitter during a Global Crisis of Volkswagen - The Case of Dieselgate

In this study, we investigate the communication behaviour in Twitter during the rise of a corporate crisis. In September 2015, the emission scandal of Volkswagen (also known as Dieselgate ) became public. We collected Twitter data and analysed approximately 400,000 tweets regarding the Volkswagen crisis. We take different perspectives on the data, by 1) separating the overall communication in peak and quiet phases, 2) analysing the sentiment in each phase, 3) looking at specific tweet contents, and 4) using statistical analyses to determine the significance of differences. Furthermore, we mapped the publishing behaviour of official Volkswagen accounts to the situational crisis communication theory (SCCT). The findings suggest that Volkswagen followed a strategy that is not covered by SCCT, i.e. keeping silent. Volkswagen’s tweets were not able to reduce the emotionality and sentiment of the ongoing Twitter discussion. Instead, even during quiet phases, the communication remained rather negative