Seminar Users in the Arabic Twitter Sphere

We introduce the notion of "seminar users", who are social media users engaged in propaganda in support of a political entity. We develop a framework that can identify such users with 84.4% precision and 76.1% recall. While our dataset is from the Arab region, omitting language-specific features has only a minor impact on classification performance, and thus, our approach could work for detecting seminar users in other parts of the world and in other languages. We further explored a controversial political topic to observe the prevalence and potential potency of such users. In our case study, we found that 25% of the users engaged in the topic are in fact seminar users and their tweets make nearly a third of the on-topic tweets. Moreover, they are often successful in affecting mainstream discourse with coordinated hashtag campaigns.Comment: to appear in SocInfo 201

Social media, political polarization, and political disinformation: a review of the scientific literature

The following report is intended to provide an overview of the current state of the literature on the relationship between social media; political polarization; and political “disinformation,” a term used to encompass a wide range of types of information about politics found online, including “fake news,” rumors, deliberately factually incorrect information, inadvertently factually incorrect information, politically slanted information, and “hyperpartisan” news. The review of the literature is provided in six separate sections, each of which can be read individually but that cumulatively are intended to provide an overview of what is known — and unknown — about the relationship between social media, political polarization, and disinformation. The report concludes by identifying key gaps in our understanding of these phenomena and the data that are needed to address them

Social media, political polarization, and political disinformation: a review of the scientific literature

The following report is intended to provide an overview of the current state of the literature on the relationship between social media; political polarization; and political “disinformation,” a term used to encompass a wide range of types of information about politics found online, including “fake news,” rumors, deliberately factually incorrect information, inadvertently factually incorrect information, politically slanted information, and “hyperpartisan” news. The review of the literature is provided in six separate sections, each of which can be read individually but that cumulatively are intended to provide an overview of what is known — and unknown — about the relationship between social media, political polarization, and disinformation. The report concludes by identifying key gaps in our understanding of these phenomena and the data that are needed to address them

Temporal Analysis and User Characteristics of Internet Censorship on Sina Weibo

This research investigates features used to identify surveillance targets and the probability of censored posts over time on the Chinese Sina Weibo social media platform. Targets include the recency of content chosen for censorship, frequency, and the users surveilled. The analysis consists of 14,000 censored posts on Sina Weibo collected over 3 months from August to November of 2021. Results, demonstrate that during the past 10 years the rate of censorship has increased and verified users (paying customers) who have a high user ranking in the system are censored more frequently than unverified (non-paying customers) low ranking users. In time T1 there is an 80% chance of a post to be censored if it is less than 50 days old while in time T2 there is an 80% probability (dashed red line) of a post being censored occurs after 1000 days (3100 -2100)

From Virality to Veracity: Examining False Information on Telegram vs. Twitter

The COVID-19 pandemic gave rise to various false information including that Ivermectin is effective against COVID-19 disease, which spread on social media. Because Telegram\u27s structure poses a high risk for radicalization, it is imperative to understand the underlying spreading processes. Therefore, we gathered a network of German-speaking channels that spread false information about Ivermectin to analyze the network structure and the spread of false information. By comparing results from Telegram to Twitter network, important insights are gained for research and practice. Results revealed that opinion leaders play a significant role in the spreading process of false information. This is evident because false information on Telegram can reach more users and requires fewer distributors compared to Twitter. The study outlines avenues for future research regarding false information on Telegram