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Breaking Hash-Tag Detection Algorithm for Social Media (Twitter)

Abstract In trading, volume is a measure of how much stock has been exchanged in a given period of time. Since every stock is distinctive and has an alternate measure of shares, volume can be contrasted with historical volume inside a stock to spot changes. It is likewise used to affirm value patterns, breakouts, and spot potential reversals. In my thesis, I hypothesize that the concept of trading volume can be extrapolated to social media (Twitter).

The ubiquity of social media, especially Twitter, in financial market has been overly resonant in the past couple of years. With the growth of its (Twitter) usage by news channels, financial experts and pandits, the global economy does seem to hinge on 140 characters. By analyzing the number of tweets ... (more)
Created Date 2015
Contributor Awasthi, Piyush (Author) / Davulcu, Hasan (Advisor) / Tong, Hanghang (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Subject Computer science / Finance / Economics / Algorithm / hashtags / Stock Prediction / Twitter / Volume Breakout / Web Crawling
Type Masters Thesis
Extent 36 pages
Language English
Reuse Permissions All Rights Reserved
Note Masters Thesis Computer Science 2015
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis