Social Media Data Analysis
Script
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Scope And Content | config.ini ( DB connection configuration ) db/ ( Materialized View Scripts for Postgres DB ) DSE_MAS_Cohort5_Group6_README.md references.md ( external interesting articles ) pipeline/ ( pipeline python files ) yolo/ ( Yolo specific weight for the neural net model ) notebooks/ ( EDA Model collection ) visual/ ( visualization app in JS ) |
Technical Details | Python 3.7.6, Jupyter-notebook 6.0.3, YOLO 3, SigmaJS v1.2.1, various Python libs available with Anaconda (version 1.7.2) |
- Collection
- Cite This Work
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Namuduri, Vamsi; Tawashi, Mohammed; Pathuri, Hanumantha; Mohammed, Naveed; Shirkhani, Amir; Gupta, Amarnath (2020). Social Media Data Analysis. In Data Science & Engineering Master of Advanced Study (DSE MAS) Capstone Projects. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0JS9NZ5
- Description
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This project focuses on studying how Twitter images impact the narrative of hashtags. A lot of research in Twitter data has been focused on separate textual content without media attachments. Images attached to a tweet provide an additional dimension to help understand a tweet’s context and the user’s general opinion. The assumption is that the visual images reinforce the opinion that was presented in the text. The project aims at finding specific patterns in tweets where media files (images) are used to change the narrative of the corresponding hashtag and co-occurred hashtags. This is achieved by studying the topic of solo hashtag and co-occurred hashtags without or with associated media files. Media file as a visual channel is a powerful medium and can change the subject and original purpose of a hashtag for a given audience. A small number of media tweets (images) associated with a hashtag can have a higher influential impact on an observer/user than the same or even higher number of tweets without media. There are multiple benefactors to the findings from this project. 1- Election organizer as part of a campaign can study and detect endorsing and opposing trends and act by counter measures using similar techniques. 2- Social Media platform and specially Twitter itself can detect patterns and potentially restrict the behavior. 3- Journalists can report to general public on how a potential small group of influencers can sway a narrative and push various agendas.
- Creation Date
- 2020-01 to 2020-06
- Date Issued
- 2020
- Authors
- Advisor
- Note
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UCSD database holds and gathers Tweets on regular basis. Project Data is obtained from UCSD ( connect.awesome.sdsc.edu) and not directly from Twitter API.
- Series
- Topics
Formats
View formats within this collection
- Language
- English
- License
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Creative Commons Attribution-NonCommercial 4.0 International Public License
- Rights Holder
- Namuduri, Vamsi; Tawashi, Mohammed; Pathuri, Hanumantha; Mohammed, Naveed; Shirkhani, Amir
- Copyright
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Under copyright (US)
Use: This work is available from the UC San Diego Library. This digital copy of the work is intended to support research, teaching, and private study.
Constraint(s) on Use: This work is protected by the U.S. Copyright Law (Title 17, U.S.C.). Use of this work beyond that allowed by "fair use" or any license applied to this work requires written permission of the copyright holder(s). Responsibility for obtaining permissions and any use and distribution of this work rests exclusively with the user and not the UC San Diego Library. Inquiries can be made to the UC San Diego Library program having custody of the work.
- Digital Object Made Available By
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Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp)
- Last Modified
2020-10-26