Related papers: Temporal Analysis of Drifting Hashtags in Textual …

One of the major sources of trending news, events and opinion in the current age is micro blogging. Twitter, being one of them, is extensively used to mine data about public responses and event updates. This paper intends to propose methods…

Social media are being increasingly used for health promotion, yet the landscape of users, messages and interactions in such fora is poorly understood. Studies of social media and diabetes have focused mostly on patients, or public agencies…

Twitter is one of the top influenced social media which has a million number of active users. It is commonly used for microblogging that allows users to share messages, ideas, thoughts and many more. Thus, millions interaction such as short…

Since the advent of online social media platforms such as Twitter and Facebook, useful health-related studies have been conducted using the information posted by online participants. Personal health-related issues such as mental health,…

Twitter has captured the interest of the scientific community not only for its massive user base and content, but also for its openness in sharing its data. Twitter shares a free 1% sample of its tweets through the "Streaming API", a…

The rise of a trending topic on Twitter or Facebook leads to the temporal emergence of a set of users currently interested in that topic. Given the temporary nature of the links between these users, being able to dynamically identify…

We study how users of multiple online social networks (OSNs) employ and share information by studying a common user pool that use six OSNs - Flickr, Google+, Instagram, Tumblr, Twitter, and YouTube. We analyze the temporal and topical…

Social networks include millions of users constantly looking for new relationships for personal or professional purposes. Social network sites recommend friends based on relationship features and content information. A significant part of…

An active line of research has used on-line data to study the ways in which discrete units of information---including messages, photos, product recommendations, group invitations---spread through social networks. There is relatively little…

In Twitter, and other microblogging services, the generation of new content by the crowd is often biased towards immediacy: what is happening now. Prompted by the propagation of commentary and information through multiple mediums, users on…

Vast amounts of human communication occurs online. These digital traces of natural human communication along with recent advances in natural language processing technology provide for computational analysis of these discussions. In the…

The COVID-19 pandemic has affected all aspects of society, not only bringing health hazards, but also posing challenges to public order, governments and mental health. Moreover, it is the first one in history in which people from around the…

We propose an interpretable, graph-based framework for analyzing semantic shift in diachronic corpora. For each target word and time slice, we induce a word-centered semantic network that integrates distributional similarity from diachronic…

The modern news cycle has been fundamentally reshaped by the rapid exchange of information online. As a result, media framing shifts dynamically as new information, political responses, and social reactions emerge. Understanding how these…

After the COVID-19 pandemic caused internet usage to grow by 70%, there has been an increased number of people all across the world using social media. Applications like Twitter, Meta Threads, YouTube, and Reddit have become increasingly…

Language use has been shown to correlate with depression, but large-scale validation is needed. Traditional methods like clinic studies are expensive. So, natural language processing has been employed on social media to predict depression,…

With the outbreak of the Covid-19 virus, the activity of users on Twitter has significantly increased. Some studies have investigated the hot topics of tweets in this period; however, little attention has been paid to presenting and…

The #MeToo movement has catalyzed widespread public discourse surrounding sexual harassment and assault, empowering survivors to share their stories and holding perpetrators accountable. While the movement has had a substantial and largely…

The popularization of social media increases user engagements and generates a large amount of user-oriented data. Among them, text data (e.g., tweets, blogs) significantly attracts researchers and speculators to infer user attributes (e.g.,…

Large-scale data resulting from users online interactions provide the ultimate source of information to study emergent social phenomena on the Web. From individual actions of users to observable collective behaviors, different mechanisms…