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This article presents a preliminary approach towards characterizing political fake news on Twitter through the analysis of their meta-data. In particular, we focus on more than 1.5M tweets collected on the day of the election of Donald…
We analyze the relationship between partisanship, echo chambers, and vulnerability to online misinformation by studying news sharing behavior on Twitter. While our results confirm prior findings that online misinformation sharing is…
We analyze the ego-alter Twitter networks of 300 Italian MPs and 18 European leaders, and of about 14,000 generic users. We find structural properties typical of social environments, meaning that Twitter activity is controlled by…
This study uses sentiment analysis and the Moral Foundations Theory (MFT) to characterise news content in social media and examine its association with user engagement. We employ Natural Language Processing to quantify the moral and…
Understanding and mitigating political bias in online social media platforms are crucial tasks to combat misinformation and echo chamber effects. However, characterizing political bias temporally using computational methods presents…
Recent advances in machine learning have led to computer systems that are human-like in behaviour. Sentiment analysis, the automatic determination of emotions in text, is allowing us to capitalize on substantial previously unattainable…
Measuring and forecasting opinion trends from real-time social media is a long-standing goal of big-data analytics. Despite its importance, there has been no conclusive scientific evidence so far that social media activity can capture the…
Social media has become an indispensable channel for political communication. However, the political discourse is increasingly characterized by hate speech, which affects not only the reputation of individual politicians but also the…
Studying political activity on social media often requires defining and measuring political stances of users or content. Relevant examples include the study of opinion polarization, or the study of political diversity in online content…
Social media platforms are thriving nowadays, so a huge volume of data is produced. As it includes brief and clear statements, millions of people post their thoughts on microblogging sites every day. This paper represents and analyze the…
The advent of WWW changed the way we can produce and access information. Recent studies showed that users tend to select information that is consistent with their system of beliefs, forming polarized groups of like-minded people around…
Social media is often used by researchers as an approach to obtaining real-time data on people's activities and thoughts. Twitter, as one of the most popular social networking services nowadays, provides copious information streams on…
US voters shared large volumes of polarizing political news and information in the form of links to content from Russian, WikiLeaks and junk news sources. Was this low quality political information distributed evenly around the country, or…
When information flow fails, when Democrats and Republicans do not talk to each other, when Israelis and Palestinians do not talk to each other, and when North Koreans and South Koreans do not talk to each other, mis-perceptions, biases and…
Although misinformation tends to spread online, it can have serious real-world consequences. In order to develop automated tools to detect and mitigate the impact of misinformation, researchers must leverage algorithms that can adapt to the…
Sentiment analysis (or opinion mining) on Twitter data has attracted much attention recently. One of the system's key features, is the immediacy in communication with other users in an easy, user-friendly and fast way. Consequently, people…
A comprehensive understanding of data quality is the cornerstone of measurement studies in social media research. This paper presents in-depth measurements on the effects of Twitter data sampling across different timescales and different…
Social media platforms allow users to create polls to gather public opinion on diverse topics. However, we know little about what such polls are used for and how reliable they are, especially in significant contexts like elections. Focusing…
People might not be close-at-hand but they still are - by virtue of the social network. The social network has transformed lives in many ways. People can express their views, opinions and life experiences on various platforms be it Twitter,…
This paper investigates the presence of political bias in emotion inference models used for sentiment analysis (SA) in social science research. Machine learning models often reflect biases in their training data, impacting the validity of…