相关论文: Mining Half a Billion Topical Experts Across Multi…

Twitter is one of the largest social networks using exclusively directed links among accounts. This makes the Twitter social graph much closer to the social graph supporting real life communications than, for instance, Facebook. Therefore,…

People today typically use multiple online social networks (Facebook, Twitter, Google+, LinkedIn, etc.). Each online network represents a subset of their "real" ego-networks. An interesting and challenging problem is to reconcile these…

Online social networks serve as major platforms for disseminating both real and fake news. Many users--intentionally or unintentionally--spread harmful content, misinformation, and rumors in domains such as politics and business.…

Online socio-technical systems can be studied as proxy of the real world to investigate human behavior and social interactions at scale. Here we focus on Instagram, a media-sharing online platform whose popularity has been rising up to…

Social graphs, representing online friendships among users, are one of the fundamental types of data for many applications, such as recommendation, virality prediction and marketing in social media. However, this data may be unavailable due…

In this new era of social media, social networks are becoming increasingly important sources of user-generated content on the internet. These kinds of information resources, which include a lot of people's feelings, opinions, feedback, and…

Contemporary datasets on tobacco consumption focus on one of two topics, either public health mentions and disease surveillance, or sentiment analysis on topical tobacco products and services. However, two primary considerations are not…

Social networks seeded, crystallized and structured by large-scale social platforms like Facebook, LinkedIn, Slack, Twitter, WhatsApp, Instagram and WeChat exhibit complicated epistemic structures and dynamics that arise from the nature of…

With the rise of social networks, information on the internet is no longer solely organized by web pages. Rather, content is generated and shared among users and organized around their social relations on social networks. This presents new…

Online social networks have emerged as useful tools to communicate or share information and news on a daily basis. One of the most popular networks is Twitter, where users connect to each other via directed follower relationships.…

How can the birth and evolution of ideas and communities in a network be studied over time? We use a multimodal pipeline, consisting of network mapping, topic modeling, bridging centrality, and divergence to analyze Twitter data surrounding…

The problem of searching for experts in a given academic field is hugely important in both industry and academia. We study exactly this issue with respect to a database of authors and their publications. The idea is to use Latent Semantic…

We introduce the problem of proficiency modeling: Given a user's posts on a social media platform, the task is to identify the subset of posts or topics for which the user has some level of proficiency. This enables the filtering and…

The development of social media user stance detection and bot detection methods rely heavily on large-scale and high-quality benchmarks. However, in addition to low annotation quality, existing benchmarks generally have incomplete user…

Toxic sentiment analysis on Twitter (X) often focuses on specific topics and events such as politics and elections. Datasets of toxic users in such research are typically gathered through lexicon-based techniques, providing only a…

Influential users play an important role in online social networks since users tend to have an impact on one other. Therefore, the proposed work analyzes users and their behavior in order to identify influential users and predict user…

Data extracted from social media platforms, such as Twitter, are both large in scale and complex in nature, since they contain both unstructured text, as well as structured data, such as time stamps and interactions between users. A key…

On social media platforms and Twitter in particular, specific classes of users such as influencers have been given satisfactory operational definitions in terms of network and content metrics. Others, for instance online activists, are not…

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…

This paper presents Klout Topics, a lightweight ontology to describe social media users' topics of interest and expertise. Klout Topics is designed to: be human-readable and consumer-friendly; cover multiple domains of knowledge in depth;…