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What tweet features are associated with higher effectiveness in tweets? Through the mining of 122 million engagements of 2.5 million original tweets, we present a systematic review of tweet time, entities, composition, and user account…
Statistical topic models efficiently facilitate the exploration of large-scale data sets. Many models have been developed and broadly used to summarize the semantic structure in news, science, social media, and digital humanities. However,…
We present the first comprehensive characterization of the diffusion of ideas on Twitter, studying more than 4000 topics that include both popular and less popular topics. On a data set containing approximately 10 million users and a…
We address the problem of maximizing user engagement with content (in the form of like, reply, retweet, and retweet with comments)on the Twitter platform. We formulate the engagement forecasting task as a multi-label classification problem…
The discourse around conspiracy theories is currently thriving amidst the rampant misinformation in online environments. Research in this field has been focused on detecting conspiracy theories on social media, often relying on limited…
Information exchange and message diffusion have moved from traditional media to social media platforms. Messages on platforms such as Twitter have become the default mode of company communications replacing lengthier public announcements…
A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how…
Many people now watch health videos, such as diet, exercise, mental health, COVID-19, and chronic disease videos, on social media. Most existing studies focused on video creators, leaving the motivations and practices of viewers…
Social media, regarded as two-layer networks consisting of users and items, turn out to be the most important channels for access to massive information in the era of Web 2.0. The dynamics of human activity and item popularity is a crucial…
Social Search research deals with studying methodologies exploiting social information to better satisfy user information needs in Online Social Media while simplifying the search effort and consequently reducing the time spent and the…
This survey draws a broad-stroke, panoramic picture of the State of the Art (SoTA) of the research in generative methods for the analysis of social media data. It fills a void, as the existing survey articles are either much narrower in…
With over 500 million tweets posted per day, in Twitter, it is difficult for Twitter users to discover interesting content from the deluge of uninteresting posts. In this work, we present a novel, explainable, topical recommendation system,…
Centrality is one of the most studied concepts in social network analysis. There is a huge literature regarding centrality measures, as ways to identify the most relevant users in a social network. The challenge is to find measures that can…
The amount of text generated daily on social media is gigantic and analyzing this text is useful for many purposes. To understand what lies beneath a huge amount of text, we need dependable and effective computing techniques from…
As an online, crowd-sourced, open English-language slang dictionary, the Urban Dictionary platform contains a wealth of opinions, jokes, and definitions of terms, phrases, acronyms, and more. However, it is unclear exactly how activity on…
Measuring the impact and success of human performance is common in various disciplines, including art, science, and sports. Quantifying impact also plays a key role on social media, where impact is usually defined as the reach of a user's…
Twitter is increasingly used for political, advertising and marketing campaigns, where the main aim is to influence users to support specific causes, individuals or groups. We propose a novel methodology for mining and analyzing Twitter…
Smartphone applications designed to track human motion in combination with wearable sensors, e.g., during physical exercising, raised huge attention recently. Commonly, they provide quantitative services, such as personalized training…
Social media platforms provide convenient means for users to participate in multiple online activities on various contents and create fast widespread interactions. However, this rapidly growing access has also increased the diverse…
In this work, we tackle the problem of predicting entity popularity on Twitter based on the news cycle. We apply a supervised learn- ing approach and extract four types of features: (i) signal, (ii) textual, (iii) sentiment and (iv)…