相关论文: When is it Biased? Assessing the Representativenes…

Millions of people express themselves on public social media, such as Twitter. Through their posts, these people may reveal themselves as potentially valuable sources of information. For example, real-time information about an event might…

Twitter is a social media platform where users express opinions over a variety of issues. Posts offering grievances or complaints can be utilized by private/ public organizations to improve their service and promptly gauge a low-cost…

Nowadays, researchers have moved to platforms like Twitter to spread information about their ideas and empirical evidence. Recent studies have shown that social media affects the scientific impact of a paper. However, these studies only…

Computational methods to model political bias in social media involve several challenges due to heterogeneity, high-dimensional, multiple modalities, and the scale of the data. Political bias in social media has been studied in multiple…

This paper introduces a large collection of time series data derived from Twitter, postprocessed using word embedding techniques, as well as specialized fine-tuned language models. This data comprises the past five years and captures…

Maintaining the integrity of long-term data collection is an essential scientific practice. As a field evolves, so too will that field's measurement instruments and data storage systems, as they are invented, improved upon, and made…

Microblogging services like Twitter and Facebook collect millions of user generated content every moment about trending news, occurring events, and so on. Nevertheless, it is really a nightmare to find information of interest through the…

We present an intelligent, crowd-powered information collection system that automatically identifies and asks target-ed strangers on Twitter for desired information (e.g., cur-rent wait time at a nightclub). Our work includes three parts.…

Sentiment analysis is the task of automatic analysis of opinions and emotions of users towards an entity or some aspect of that entity. Political Sentiment Analysis of social media helps the political strategists to scrutinize the…

Social networks offer a ready channel for fake and misleading news to spread and exert influence. This paper examines the performance of different reputation algorithms when applied to a large and statistically significant portion of the…

Twitter (one example of microblogging) is widely being used by researchers to understand human behavior, specifically how people behave when a significant event occurs and how it changes user microblogging patterns. The changing…

Social graphs can be easily extracted from Online Social Networks. However these networks are getting larger from day to day. Sampling methods used to evaluate graph information cannot accurately extract graph properties. Furthermore Social…

Modeling online discourse dynamics is a core activity in understanding the spread of information, both offline and online, and emergent online behavior. There is currently a disconnect between the practitioners of online social media…

In the last decade, social networks became most popular medium for communication and interaction. As an example, micro-blogging service Twitter has more than 200 million registered users who exchange more than 65 million posts per day.…

In recent years, offensive, abusive and hateful language, sexism, racism and other types of aggressive and cyberbullying behavior have been manifesting with increased frequency, and in many online social media platforms. In fact, past…

Recommender systems constitute the core engine of most social network platforms nowadays, aiming to maximize user satisfaction along with other key business objectives. Twitter is no exception. Despite the fact that Twitter data has been…

Approximately 50% of tweets in X's user timelines are personalized recommendations from accounts they do not follow. This raises a critical question: What political content are users exposed to beyond their established networks, and what…

Statistical inference using social sensors is an area that has witnessed remarkable progress and is relevant in applications including localizing events for targeted advertising, marketing, localization of natural disasters and predicting…

Streams of user-generated content in social media exhibit patterns of collective attention across diverse topics, with temporal structures determined both by exogenous factors and endogenous factors. Teasing apart different topics and…

Online social networking services allow their users to post content in the form of text, images or videos. The main mechanism driving content diffusion is the possibility for users to re-share the content posted by their social connections,…