Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Evaluation Of Topic Models For Content-Based Popularity Prediction On Social Microblogs, Axel Magnuson
Evaluation Of Topic Models For Content-Based Popularity Prediction On Social Microblogs, Axel Magnuson
Boise State University Theses and Dissertations
Online social networks are an increasingly central medium of communication in the 21st century. We have seen a proliferation of competing social networks which differentiate themselves by serving different niches of communication. Among these, Twitter has risen to prominence as a leader among microblogging communities, characterized by publicly visible 140-character messages called tweets. The wide visibility of Twitter messages has enabled some users to curate large followings, and has facilitated content creators who wish to reach as many viewers as possible. Researchers have since investigated many methods for predicting which messages will become popular or even go viral on Twitter. …
Analysis And Simulation Of A Social Network, Twitter: A Case Study, Jonatan Reyes
Analysis And Simulation Of A Social Network, Twitter: A Case Study, Jonatan Reyes
Theses and Dissertations
The use of online social networks empowers its users to efficiently disseminate information across traditional social networks. Typically, the weight and value of messages are relative to its readers’ culture and interests. Nevertheless, in some instances, messages take the form of viral phenomenon, which circulates around the world in very short periods of time. Therefore, despite the actual content of the message spread over the network, the determination of the effectiveness of message dissemination across the social network becomes an attractive opportunity for scientific study. Since a meticulous analysis of a complete online social network would require the acquisition of …
Personalized And Adaptive Semantic Information Filtering For Social Media, Pavan Kapanipathi
Personalized And Adaptive Semantic Information Filtering For Social Media, Pavan Kapanipathi
Browse all Theses and Dissertations
Social media has experienced immense growth in recent times. These platforms are becoming increasingly common for information seeking and consumption, and as part of its growing popularity, information overload pose a significant challenge to users. For instance, Twitter alone generates around 500 million tweets per day and it is impractical for users to have to parse through such an enormous stream to find information that are interesting to them. This situation necessitates efficient personalized filtering mechanisms for users to consume relevant, interesting information from social media. Building a personalized filtering system involves understanding users' interests and utilizing these interests to …