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Sentiment Analysis on Financial News...

Talekar, Chinmay.

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Sentiment Analysis on Financial News and Microblogs.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Sentiment Analysis on Financial News and Microblogs./
Author:	Talekar, Chinmay.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	73 p.
Notes:	Source: Masters Abstracts International, Volume: 79-12.
Contained By:	Masters Abstracts International79-12.
Subject:	Linguistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10807982
ISBN:	9780438012561

Sentiment Analysis on Financial News and Microblogs.
Talekar, Chinmay.

Sentiment Analysis on Financial News and Microblogs. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 73 p.

Source: Masters Abstracts International, Volume: 79-12.

Thesis (M.S.)--Purdue University, 2018.

This item must not be sold to any third party vendors.

Sentiment analysis is useful for multiple tasks including customer satisfaction metrics, identifying market trends for any industry or products, analyzing reviews from social media comments. This thesis highlights the importance of sentiment analysis, provides a summary of seminal works and different approaches towards sentiment analysis. It aims to address sentiment analysis on financial news and microblogs by classifying textual data from financial news and microblogs as positive or negative. Sentiment analysis is performed by making use of paragraph vectors and logistic regression in this thesis and it aims to compare it with previously performed approaches to performing analysis and help researchers in this field. This approach achieves state of the art results for the dataset used in this research. It also presents an insightful analysis of the results of this approach.

ISBN: 9780438012561Subjects--Topical Terms:

524476
Linguistics.

Sentiment Analysis on Financial News and Microblogs.
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245 1 0 $a Sentiment Analysis on Financial News and Microblogs.
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300 $a 73 p.
500 $a Source: Masters Abstracts International, Volume: 79-12.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Rayz, Julia.
502 $a Thesis (M.S.)--Purdue University, 2018.
506 $a This item must not be sold to any third party vendors.
520 $a Sentiment analysis is useful for multiple tasks including customer satisfaction metrics, identifying market trends for any industry or products, analyzing reviews from social media comments. This thesis highlights the importance of sentiment analysis, provides a summary of seminal works and different approaches towards sentiment analysis. It aims to address sentiment analysis on financial news and microblogs by classifying textual data from financial news and microblogs as positive or negative. Sentiment analysis is performed by making use of paragraph vectors and logistic regression in this thesis and it aims to compare it with previously performed approaches to performing analysis and help researchers in this field. This approach achieves state of the art results for the dataset used in this research. It also presents an insightful analysis of the results of this approach.
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