Related papers: Comparative Analysis of Content-based Personalized…
Large-scale databases of human activity in social media have captured scientific and policy attention, producing a flood of research and discussion. This paper considers methodological and conceptual challenges for this emergent field, with…
One of the main challenges in recommender systems is data sparsity which leads to high variance. Several attempts have been made to improve the bias-variance trade-off using auxiliary information. In particular, document modeling-based…
A set of 1.4 million biomedical papers was analyzed with regards to how often articles are mentioned on Twitter or saved by users on Mendeley. While Twitter is a microblogging platform used by a general audience to distribute information,…
Analysts and social scientists in the humanities and industry require techniques to help visualize large quantities of microblogging data. Methods for the automated analysis of large scale social media data (on the order of tens of millions…
Social networks have become an increasingly common abstraction to capture the interactions of individual users in a number of everyday activities and applications. As a result, the analysis of such networks has attracted lots of attention…
Research shows that exposure to suicide-related news media content is associated with suicide rates, with some content characteristics likely having harmful and others potentially protective effects. Although good evidence exists for a few…
To analyse large numbers of texts, social science researchers are increasingly confronting the challenge of text classification. When manual labeling is not possible and researchers have to find automatized ways to classify texts, computer…
Recommendation systems are widely used in web services, such as social networks and e-commerce platforms, to serve personalized content to the users and, thus, enhance their experience. While personalization assists users in navigating…
The proliferation of social media has the potential for changing the structure and organization of the web. In the past, scientists have looked at the web as a large connected component to understand how the topology of hyperlinks…
Popularity of content in social media is unequally distributed, with some items receiving a disproportionate share of attention from users. Predicting which newly-submitted items will become popular is critically important for both hosts of…
Social media platforms bring together content creators and content consumers through recommender systems like newsfeed. The focus of such recommender systems has thus far been primarily on modeling the content consumer preferences and…
TikTok currently is the fastest growing social media platform with over 1 billion active monthly users of which the majority is from generation Z. Arguably, its most important success driver is its recommendation system. Despite 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…
The rise in popularity of social media platforms, has resulted in millions of new, content pieces being created every day. This surge in content creation underscores the need to pay attention to our design choices as they can greatly impact…
Nowadays, massive useful data of user information and social behavior have been accumulated on the Internet, providing a possibility of profiling user's personality traits online. In this paper, we propose a psychological modeling method…
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…
Web applications are increasingly showing recommended users from social media along with some descriptions, an attempt to show relevancy - why they are being shown. For example, Twitter search for a topical keyword shows expert twitterers…
Large quantities of data flow on the internet. When a user decides to help the spread of a piece of information (by retweeting, liking, posting content), most research works assumes she does so according to information's content,…
Social media platforms provide users with a profile description field, commonly known as a ``bio," where they can present themselves to the world. A growing literature shows that text in these bios can improve our understanding of online…
User-generated, multi-paragraph writing is pervasive and important in many social media platforms (i.e. Amazon reviews, AirBnB host profiles, etc). Ensuring high-quality content is important. Unfortunately, content submitted by users is…