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 patte...
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ndltd-asu.edu-item-298382018-06-22T03:06:08Z 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 hash tagged to a stock, a strong relation can be established between the number of people talking about it, to the trading volume of the stock. In my work, I overt this relation and find a state of the breakout when the volume goes beyond a characterized support or resistance level. Dissertation/Thesis Awasthi, Piyush (Author) Davulcu, Hasan (Advisor) Tong, Hanghang (Committee member) Sen, Arunabha (Committee member) Arizona State University (Publisher) Computer science Finance Economics Algorithm hashtags Stock Prediction Twitter Volume Breakout Web Crawling eng 36 pages Masters Thesis Computer Science 2015 Masters Thesis http://hdl.handle.net/2286/R.I.29838 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2015 |
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English |
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Dissertation |
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Computer science Finance Economics Algorithm hashtags Stock Prediction Volume Breakout Web Crawling |
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Computer science Finance Economics Algorithm hashtags Stock Prediction Volume Breakout Web Crawling Breaking Hash-Tag Detection Algorithm for Social Media (Twitter) |
description |
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 hash tagged to a stock, a strong relation can be established between the number of people talking about it, to the trading volume of the stock.
In my work, I overt this relation and find a state of the breakout when the volume goes beyond a characterized support or resistance level. === Dissertation/Thesis === Masters Thesis Computer Science 2015 |
author2 |
Awasthi, Piyush (Author) |
author_facet |
Awasthi, Piyush (Author) |
title |
Breaking Hash-Tag Detection Algorithm for Social Media (Twitter) |
title_short |
Breaking Hash-Tag Detection Algorithm for Social Media (Twitter) |
title_full |
Breaking Hash-Tag Detection Algorithm for Social Media (Twitter) |
title_fullStr |
Breaking Hash-Tag Detection Algorithm for Social Media (Twitter) |
title_full_unstemmed |
Breaking Hash-Tag Detection Algorithm for Social Media (Twitter) |
title_sort |
breaking hash-tag detection algorithm for social media (twitter) |
publishDate |
2015 |
url |
http://hdl.handle.net/2286/R.I.29838 |
_version_ |
1718700742922993664 |