Advisory Committee Chair
Dale W Callahan
Advisory Committee Members
Olivia Affuso
Allen C Johnston
Roy P Koomullil
Murat M Tanik
Document Type
Dissertation
Date of Award
2015
Degree Name by School
Doctor of Philosophy (PhD) School of Engineering
Abstract
Social Media (SM) is becoming a normal part of everyday life for many people around the world. This new form of communication has helped to close social gaps and bring the world closer. The information generated from Social Networking Sites (SNS) is increasingly utilized as a communication channel for market trend, brand awareness, breaking news, person-to-person online social interaction, etc. As more and more people are using SNS, their reach and power are growing rapidly in daily life. Massive amounts of daily data generated from SNS can be used in many interdisciplinary areas of research such as the Humanities, Art, Science, Engineering, Sports, etc. SM data is readily available through SNS’s Application Programming Interface (API). Many SNS provide deeper statistical information to further this research into SM data. In the recent years, events have been continuously discussed on SM in the form of status updates, posts, discussions and comments by its participants, volunteers, and supporters. SM content generated before, during, and after an event could add valuable insight into the success, popularity, ideas for future improvement of the event, etc. With the fast evolving nature of SM, current events’ SM content is ignored, forgotten, and overlooked for new sets of future posts, discussions, and comments. This dissertation research demonstrates that any publically available SM data can be captured and analyzed to produce a numeric rating for an event such as a marathon. As a result, a rating model was created through combinations of multiple models using SM data to rate an event. Key words: Social Media (SM), Social Networking Site (SNS), Rating System, Sentiment Analysis, Marathon, Twitter, Hashtag (#), Rating Model, Rating, Tweet
Recommended Citation
Silwal, Suman, "Developing A Rating Model Using Social Media Data" (2015). All ETDs from UAB. 2973.
https://digitalcommons.library.uab.edu/etd-collection/2973
