Detecting sentiment in Twitter data – challenges and implementation

Twitter is one of the most popular micro-blogging platforms where users publish their thoughts and opinions and much attention is paid to explore sentiment of these opinions. This paper focuses on the characteristic of Twitter, tweets and supervised machine-learning method for Twitter Sentiment Anal...

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Bibliographic Details
Main Author:	Joanna Michalak
Format:	Article
Language:	English
Published:	WSB University in Torun 2016-12-01
Series:	Torun Business Review
Online Access:	https://tbr.wsb.torun.pl/index.php/journal/article/view/71

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spelling	doaj-d372e771194e4abb97736aff693bd1d02020-11-25T00:19:41ZengWSB University in TorunTorun Business Review1643-81752451-09552016-12-011549711010.19197/tbr.v15i4.7156Detecting sentiment in Twitter data – challenges and implementationJoanna Michalak0Nicolaus Copernicus University in Torun ul. Gagarina 13a 87-100 ToruńTwitter is one of the most popular micro-blogging platforms where users publish their thoughts and opinions and much attention is paid to explore sentiment of these opinions. This paper focuses on the characteristic of Twitter, tweets and supervised machine-learning method for Twitter Sentiment Analysis. Discussion focuses on the following issues: access to the tweets and creating a database, the process of cleaning the database and process of tweets classification into positive and negative groups. The TSA process is presented in Python by simplified architecture.https://tbr.wsb.torun.pl/index.php/journal/article/view/71
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Joanna Michalak
spellingShingle	Joanna Michalak Detecting sentiment in Twitter data – challenges and implementation Torun Business Review
author_facet	Joanna Michalak
author_sort	Joanna Michalak
title	Detecting sentiment in Twitter data – challenges and implementation
title_short	Detecting sentiment in Twitter data – challenges and implementation
title_full	Detecting sentiment in Twitter data – challenges and implementation
title_fullStr	Detecting sentiment in Twitter data – challenges and implementation
title_full_unstemmed	Detecting sentiment in Twitter data – challenges and implementation
title_sort	detecting sentiment in twitter data – challenges and implementation
publisher	WSB University in Torun
series	Torun Business Review
issn	1643-8175 2451-0955
publishDate	2016-12-01
description	Twitter is one of the most popular micro-blogging platforms where users publish their thoughts and opinions and much attention is paid to explore sentiment of these opinions. This paper focuses on the characteristic of Twitter, tweets and supervised machine-learning method for Twitter Sentiment Analysis. Discussion focuses on the following issues: access to the tweets and creating a database, the process of cleaning the database and process of tweets classification into positive and negative groups. The TSA process is presented in Python by simplified architecture.
url	https://tbr.wsb.torun.pl/index.php/journal/article/view/71
work_keys_str_mv	AT joannamichalak detectingsentimentintwitterdatachallengesandimplementation
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Detecting sentiment in Twitter data – challenges and implementation

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