Related papers: Regression and Learning to Rank Aggregation for Us…
Most previous analysis of Twitter user behavior is focused on individual information cascades and the social followers graph. We instead study aggregate user behavior and the retweet graph with a focus on quantitative descriptions. We find…
We present a new machine learning and text information extraction approach to detection of cyber threat events in Twitter that are novel (previously non-extant) and developing (marked by significance with respect to similarity with a…
The rise in popularity and ubiquity of Twitter has made sentiment analysis of tweets an important and well-covered area of research. However, the 140 character limit imposed on tweets makes it hard to use standard linguistic methods for…
Many years after online social networks exceeded our collective attention, social influence is still built on attention capital. Quality is not a prerequisite for viral spreading, yet large diffusion cascades remain the hallmark of a social…
Sociologists associate the spatial variation of crime within an urban setting, with the concept of collective efficacy. The collective efficacy of a neighborhood is defined as social cohesion among neighbors combined with their willingness…
Since internet technologies have advanced, one of the primary factors in company development is customer happiness. Online platforms have become prominent places for sharing reviews. Twitter is one of these platforms where customers…
We can often detect from a person's utterances whether he/she is in favor of or against a given target entity -- their stance towards the target. However, a person may express the same stance towards a target by using negative or positive…
Analyzing following behavior is important in many applications. Following behavior may depend on the main intention of the follower. Users may either follow their friends or they may follow celebrities to know more about them. It is…
Analysing sentiment of tweets is important as it helps to determine the users' opinion. Knowing people's opinion is crucial for several purposes starting from gathering knowledge about customer base, e-governance, campaigning and many more.…
Inferring socioeconomic attributes of social media users such as occupation and income is an important problem in computational social science. Automated inference of such characteristics has applications in personalised recommender…
Twitter is among the most prevalent social media platform being used by millions of people all over the world. It is used to express ideas and opinions about political, social, business, sports, health, religion, and various other…
In the last couple decades, social network services like Twitter have generated large volumes of data about users and their interests, providing meaningful business intelligence so organizations can better understand and engage their…
As a YouTube channel grows, each video can potentially collect enormous amounts of comments that provide direct feedback from the viewers. These comments are a major means of understanding viewer expectations and improving channel…
Twitter, a microblogging service, is todays most popular platform for communication in the form of short text messages, called Tweets. Users use Twitter to publish their content either for expressing concerns on information news or views on…
Traditional sentiment analysis approaches tackle problems like ternary (3-category) and fine-grained (5-category) classification by learning the tasks separately. We argue that such classification tasks are correlated and we propose a…
An effective ranking model usually requires a large amount of training data to learn the relevance between documents and queries. User clicks are often used as training data since they can indicate relevance and are cheap to collect, but…
Microblogging websites, especially Twitter have become an important means of communication, in today's time. Often these services have been found to be faster than conventional news services. With millions of users, a need was felt to…
Social media datasets, especially Twitter tweets, are popular in the field of text classification. Tweets are a valuable source of micro-text (sometimes referred to as "micro-blogs"), and have been studied in domains such as sentiment…
In this paper we present our 2nd place solution to ACM RecSys 2021 Challenge organized by Twitter. The challenge aims to predict user engagement for a set of tweets, offering an exceptionally large data set of 1 billion data points sampled…
In a pre-registered algorithmic audit, we found that, relative to a reverse-chronological baseline, Twitter's engagement-based ranking algorithm amplifies emotionally charged, out-group hostile content that users say makes them feel worse…