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Nowadays, Twitter is an important source of information and latest updates during ongoing events, such as disaster events. However, the huge number of tweets posted during a disaster makes identification of relevant information highly challenging. ...

Encouraging prosocial tendencies toward others' physical appearance is crucial for promoting a positive body image during adolescence. Social media content that highlights positive appearance messages can significantly influence these tendencies. ...

• Over time, prosocial tendencies correlated with more prosocial reasoning, BoPo exposure and posting positive comments.
• BoPo and positive appearance comments did not consistently impact appearance-related prosocial reasoning and ...

We investigated whether individuals driven by power motives are more inclined to disseminate (mis)information within their online networks. Four studies (N = 1882) assessed or manipulated chronic and context-specific power motives, alongside ...

• Power motivated social media users overshared other people's posts and newsheadlines, including misinformation.
• Power motivated social media users disproportionately spread misinformation.
• They were more aware of having spread ...

Despite the wealth of literature vested in the association between social media use and vulnerability to fake news, it remains underexplored how and what kinds of social media usage contribute to fake news susceptibility. To fill this research ...

• News-Finds-Me was prevalent among respondents.
• News-Finds-Me was positively associated with the third-person perception fallacy of fake news vulnerability.
• News-Finds-Me significantly increased fake news vulnerability through the ...

In the digital age, online security and authenticity face serious issues due to the widespread use of fraudulent personas on social media sites. This research article outlines a comprehensive methodology for detecting fake profiles, starting with ...

This research addresses the critical gap in bushfire evacuation studies: the lack of empirical data on human behavior during evacuations. Social media platforms offer a rich source of data, but effectively mining and analyzing this data presents ...

Social platforms are vital for information dissemination but also contribute to the spread of fake news, causing confusion and misinformation. To combat this, advancements in detection technology are crucial, particularly for posts that combine ...

The rapid evolution of the digital era has greatly transformed social media, resulting in more diverse emotional expressions and increasingly complex public discourse. Consequently, identifying relationships within multimodal data has become ...

Cyberbullying detection refers to the process of classifying and identifying of cyberbullying behavior—which involves the use of technology to harass, or bullying individuals, typically through online platforms. A growing concern is the spread of ...

Online social media has revolutionized human interaction by fostering unparalleled cooperation and connectivity, surpassing the bounds of conventional, location-based methods. Despite their inherent limitations—such as physical boundaries, ongoing ...

The emergence of multimodal data on social media platforms presents new opportunities to better understand user sentiments toward a given aspect. However, existing multimodal datasets for aspect-category sentiment analysis (ACSA) often focus on ...

The relationship between propaganda campaigns, news outlets, and search patterns is of significant interest to political authorities and academic scholars from various disciplines. We explore these dynamic relationships using 3,500 Facebook propaganda ...

A common form of analysis of textual data is entity co-occurrence, where networks of entities and their connections within the text are constructed and their topology analysed. As the analysis is focused on the entities and their relations, the ...

Social media plays an important role in expressing the thoughts and sentiments of users. Irony is a way of stating a sentiment about something by expressing the opposite of the intended literal meaning. Irony detection is a recent emerging task in low-...

Discovering knowledge from social media becomes a trend in many domains such as tourism, where users' feedback and rating are the basis of recommendation systems. In this context, cluster analysis has been a major tool to disclose user groups by ...

Multimodal Named Entity Recognition (MNER) aims to identify entities of predefined types in text by leveraging information from multiple modalities, most notably textual and visual information. Most efforts concentrate on improving cross-modality ...

• Propose a model for Multimodal NER using instruction and external knowledge.
• Construct multimodal instruction for effective cross-modal feature fusion.
• Utilize Visual-Language Model to mine the implicit interaction between ...

• Women use social media to engage with fitness in four main ways, Producing, Observing, Interacting and Managing.
• Users often feel a pressure to share themselves and their perfect body for material gains including followers and ...

Social media has transformed how users create, share, and consume health and fitness content. Research to date demonstrates that despite positive sharing opportunities, women are subject to misinformation, gendered harassment, and economic ...

Most existing methods for detecting fraudulent news or other forms of disinformation primarily rely on user profiling or content analysis, determining whether a given article aligns with a user’s stylistic or content-related preferences. This ...

K-pop idols meticulously manage their public image on social media by blending aspects of professional and personal self-presentation, occasionally incorporating paid advertisements. This research aims to investigate these strategies on idols’ ...

• Revealed K-pop idols' dual self-presentation and integration of paid advertisements.
• Investigated the influence of post types on fan engagement with idols' posts.
• Found higher fan engagement with personal self-presentation posts.

The present paper introduces a novel approach to studying social media habits through predictive modeling of sequential smartphone user behaviors. While much of the literature on media and technology habits has relied on self-report ...

• The study introduces a novel conceptualization of social media habits based on the predictability of app use behaviors.
• LSTM and transformer neural networks can predict momentary social media use from app log sequences.
• There are ...