Conference proceeding
Sentiment Analysis of Twitter Samples that Differientiates Impact of User Participation Levels
2018 IEEE INTERNATIONAL CONFERENCE ON COGNITIVE COMPUTING (ICCC)
01 Jan 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The microblogging social media platform Twitter, accounting for millions of 'tweets' per day, provides an effective platform for sampling conversations on a wide array of topics and influences a variety of research areas. Coupled with the presupposition that online conversations often mirror offline conversations, many researchers leverage Twitter samples to justify conclusions about the larger population. More recently, researchers are sampling Twitter for sentiment analysis or opinion mining on products and services and, relevant to this work, for political and social commentary that may lead to election prediction. Traditionally, sentiment analysis has been visualized as an aggregation of opinions expressed in the content discussed online, while neglecting the presence of the creators of the content and the impact of their varying levels of participation. This paper illustrates and proposes an alternative model for evaluating and visualizing sentiment using Twitter samples while leveraging and highlighting user participation and impact.
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Details
- Title
- Sentiment Analysis of Twitter Samples that Differientiates Impact of User Participation Levels
- Creators
- Kimberley Hemmings-Jarrett - Drexel UniversityJulian Jarrett - Drexel UniversityM. Brian Blake - Drexel UniversityIEEE
- Publication Details
- 2018 IEEE INTERNATIONAL CONFERENCE ON COGNITIVE COMPUTING (ICCC)
- Publisher
- IEEE
- Number of pages
- 8
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000446010800009
- Scopus ID
- 2-s2.0-85054789953
- Other Identifier
- 991019319080404721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Theory & Methods