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Breaking Hash-Tag Detection Algorith...

Arizona State University.

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Breaking Hash-Tag Detection Algorithm for Social Media (Twitter).
Author:	Awasthi, Piyush.
Description:	36 p.
Notes:	Source: Masters Abstracts International, Volume: 54-04.
Notes:	Adviser: Hasan Davulcu.
Contained By:	Masters Abstracts International54-04(E).
Subject:	Computer science.
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1587804
ISBN:	9781321721331

Breaking Hash-Tag Detection Algorithm for Social Media (Twitter).
Awasthi, Piyush.

Breaking Hash-Tag Detection Algorithm for Social Media (Twitter). - 36 p.

Source: Masters Abstracts International, Volume: 54-04.

Thesis (M.S.)--Arizona State University, 2015.

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).

ISBN: 9781321721331Subjects--Topical Terms:

199325
Computer science.

Breaking Hash-Tag Detection Algorithm for Social Media (Twitter).
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245 1 0 $a Breaking Hash-Tag Detection Algorithm for Social Media (Twitter).
300 $a 36 p.
500 $a Source: Masters Abstracts International, Volume: 54-04.
500 $a Adviser: Hasan Davulcu.
502 $a Thesis (M.S.)--Arizona State University, 2015.
520 $a 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).
520 $a 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.
520 $a 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.
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