相关论文: Uncovering the Sociodemographic Fabric of Reddit

Many Web platforms rely on user collaboration to generate high-quality content: Wiki, Q&A communities, etc. Understanding and modeling the different collaborative behaviors is therefore critical. However, collaboration patterns are…

The irreplaceable key to the triumph of Question & Answer (Q&A) platforms is their users providing high-quality answers to the challenging questions posted across various topics of interest. From more than a decade, the expert finding…

We explore linguistic and behavioral features of dogmatism in social media and construct statistical models that can identify dogmatic comments. Our model is based on a corpus of Reddit posts, collected across a diverse set of…

The detection of online influence operations -- coordinated campaigns by malicious actors to spread narratives -- has traditionally depended on content analysis or network features. These approaches are increasingly brittle as generative…

Millions of people use online social networks to reinforce their sense of belonging, for example by giving and asking for feedback as a form of social validation and self-recognition. It is common to observe disagreement among people…

Accurately estimating how users respond to moderation interventions is paramount for developing effective and user-centred moderation strategies. However, this requires a clear understanding of which user characteristics are associated with…

Lately, studying social dynamics in interacting agents has been boosted by the power of computer models, which bring the richness of qualitative work, while offering the precision, transparency, extensiveness, and replicability of…

In this paper we address the task of gender classification on picture sharing social media networks such as Instagram and Flickr. We aim to infer the gender of an user given only a small set of the images shared in its profile. We make the…

Computational social science studies often contextualize content analysis within standard demographics. Since demographics are unavailable on many social media platforms (e.g. Twitter) numerous studies have inferred demographics…

We analyze gendered communities defined in three different ways: text, users, and sentiment. Differences across these representations reveal facets of communities' distinctive identities, such as social group, topic, and attitudes. Two…

Online communities play a critical role in shaping societal discourse and influencing collective behavior in the real world. The tendency for people to connect with others who share similar characteristics and views, known as homophily,…

Rules are a critical component of the functioning of nearly every online community, yet it is challenging for community moderators to make data-driven decisions about what rules to set for their communities. The connection between a…

In the era of social media platforms, identifying the credibility of online content is crucial to combat misinformation. We present the CREDiBERT (CREDibility assessment using Bi-directional Encoder Representations from Transformers), a…

Part of speech tagging is a fundamental NLP task often regarded as solved for high-resource languages such as English. Current state-of-the-art models have achieved high accuracy, especially on the news domain. However, when these models…

The objective of this study is to understand the online Ask the Doctor services medical advice on internet platforms via AskDoc, a Reddit community that serves as a public AtD platform and study if platforms mirror existing hurdles and…

Inspired by diachronic word analysis from the field of natural language processing, we propose an approach for uncovering temporal insights regarding user roles from social networks using graph embedding methods. Specifically, we apply the…

A community's identity defines and shapes its internal dynamics. Our current understanding of this interplay is mostly limited to glimpses gathered from isolated studies of individual communities. In this work we provide a systematic…

The proliferation of social media platforms has afforded social scientists unprecedented access to vast troves of data on human interactions, facilitating the study of online behavior at an unparalleled scale. These platforms typically…

Sarcasm is common in online discussions, yet difficult for machines to identify because the intended meaning often contradicts the literal wording. In this work, I study sarcasm detection using only classical machine learning methods and…

Many researchers studying online communities seek to make them better. However, beyond a small set of widely-held values, such as combating misinformation and abuse, determining what 'better' means can be challenging, as community members…