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Social media is daily creating massive multimedia content with paired image and text, presenting the pressing need to automate the vision and language understanding for various multimodal classification tasks. Compared to the commonly…
Recent studies, targeting Facebook, showed the tendency of users to interact with information adhering to their preferred narrative and to ignore dissenting information. Primarily driven by confirmation bias, users tend to join polarized…
This paper explores integrating microlearning strategies into university curricula, particularly in computer science education, to counteract the decline in class attendance and engagement in US universities after COVID. As students…
This study contributes to the literature by considering the difference in vocabulary used to express document content and information needs. Users are integrated into all research phases in order to provide them with relevant information…
Social media feed algorithms infer user preferences from their past behaviors. Yet what drives engagement often diverges from what users value. We examine this gap between stated preferences (what users say they prefer) and revealed…
Readers take decisions about going through the complete news based on many factors. The emotional impact of the news title on reader is one of the most important factors. Cognitive ergonomics tries to strike the balance between work,…
Social media is increasingly being used as a news-platform. To reach their intended audience, newspapers need for their articles to be well ranked by Facebook's news-feed algorithm. The number of likes, shares and other reactions determine…
News recommendation is one of the most challenging tasks in recommender systems, mainly due to the ephemeral relevance of news to users. As social media, and particularly microblogging applications like Twitter or Weibo, gains popularity as…
Social media platforms are increasingly deploying complex interventions to help users detect false news. Labeling false news using techniques that combine crowd-sourcing with artificial intelligence (AI) offers a promising way to inform…
Facebook News Feed personalization algorithm has a significant impact, on a daily basis, on the lifestyle, mood and opinion of millions of Internet users. Nonetheless, the behavior of such algorithm lacks transparency, motivating…
With the prevalence of misinformation online, researchers have focused on developing various machine learning algorithms to detect fake news. However, users' perception of machine learning outcomes and related behaviors have been widely…
Critical news reading (CNR), which requires grasping the holistic ideas of and raising critical thoughts on the news, is beneficial yet challenging for general people who usually get information on daily social media. Comments under the…
We describe Quizz, a gamified crowdsourcing system that simultaneously assesses the knowledge of users and acquires new knowledge from them. Quizz operates by asking users to complete short quizzes on specific topics; as a user answers the…
Given the massive market of advertising and the sharply increasing online multimedia content (such as videos), it is now fashionable to promote advertisements (ads) together with the multimedia content. It is exhausted to find relevant ads…
Usage of emoji in social media platforms has seen a rapid increase over the last few years. Majority of the social media posts are laden with emoji and users often use more than one emoji in a single social media post to express their…
In this paper we present a novel interactive multimodal learning system, which facilitates search and exploration in large networks of social multimedia users. It allows the analyst to identify and select users of interest, and to find…
Understanding and representing webpages is crucial to online social networks where users may share and engage with URLs. Common language model (LM) encoders such as BERT can be used to understand and represent the textual content of…
With the rise in use of social media to promote branded products, the demand for effective influencer marketing has increased. Brands are looking for improved ways to identify valuable influencers among a vast catalogue; this is even more…
Nowadays, artificial intelligence algorithms are used for targeted and personalized content distribution in the large scale as part of the intense competition for attention in the digital media environment. Unfortunately, targeted…
This study investigates the impact of dynamic user profile embedding on personalized context-aware experiences in social networks. A comparative analysis of multilingual and English transformer models was performed on a dataset of over…