Opinion mining using live Twitter data

Andleeb Aslam; Usman Qamar; Reda Ayesha Khan; Pakizah Saqib; Aleena Ahmad; Aiman Qadeer

doi:10.1109/CSE/EUC.2019.00016

Opinion mining using live Twitter data

Andleeb Aslam
, Usman Qamar
, Reda Ayesha Khan
, Pakizah Saqib
, Aleena Ahmad
, Aiman Qadeer

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Scopus citations

Abstract

Opinion mining and extracting Sentiments of people is the need of today. This is the era of Big data. Because of social networking sites, it's easy to analyze sentiments of people. Sentiment analysis is a technique to extract opinions of people regarding any product, issue or personality. This paper is about extracting live twitter data regarding any topic and converting it into structured form from un-structured one. Opinions are extracted from the text data and polarity is assigned against each tweet. Polarity of data can be positive, negative or neutral. Most recent and popular opinions can be extracted. It is useful for both market analyzers as well as customers. Customers get to know honest reviews about any product and companies can know their customer's interests. Furthermore, predictions are also given based on the classified data.

Original language	English
Title of host publication	Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019
Editors	Meikang Qiu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	36-39
Number of pages	4
ISBN (Electronic)	9781728116631
DOIs	https://doi.org/10.1109/CSE/EUC.2019.00016
State	Published - Aug 2019
Externally published	Yes
Event	22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019 - New York, United States Duration: 1 Aug 2019 → 3 Aug 2019

Publication series

Name	Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019

Conference

Conference	22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019
Country/Territory	United States
City	New York
Period	1/08/19 → 3/08/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Opinion Mining
Polarity
Sentiment Analysis
Twitter
Twitter Data

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Computer Vision and Pattern Recognition
Hardware and Architecture
Human-Computer Interaction
Artificial Intelligence

Access to Document

10.1109/CSE/EUC.2019.00016

Cite this

Aslam, A., Qamar, U., Khan, R. A., Saqib, P., Ahmad, A., & Qadeer, A. (2019). Opinion mining using live Twitter data. In M. Qiu (Ed.), Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019 (pp. 36-39). Article 8919578 (Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSE/EUC.2019.00016

Aslam, Andleeb ; Qamar, Usman ; Khan, Reda Ayesha et al. / Opinion mining using live Twitter data. Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019. editor / Meikang Qiu. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 36-39 (Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019).

@inproceedings{b1877fca91bc447c9f2e9b030071d026,

title = "Opinion mining using live Twitter data",

abstract = "Opinion mining and extracting Sentiments of people is the need of today. This is the era of Big data. Because of social networking sites, it's easy to analyze sentiments of people. Sentiment analysis is a technique to extract opinions of people regarding any product, issue or personality. This paper is about extracting live twitter data regarding any topic and converting it into structured form from un-structured one. Opinions are extracted from the text data and polarity is assigned against each tweet. Polarity of data can be positive, negative or neutral. Most recent and popular opinions can be extracted. It is useful for both market analyzers as well as customers. Customers get to know honest reviews about any product and companies can know their customer's interests. Furthermore, predictions are also given based on the classified data.",

keywords = "Opinion Mining, Polarity, Sentiment Analysis, Twitter, Twitter Data",

author = "Andleeb Aslam and Usman Qamar and Khan, \{Reda Ayesha\} and Pakizah Saqib and Aleena Ahmad and Aiman Qadeer",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019 ; Conference date: 01-08-2019 Through 03-08-2019",

year = "2019",

month = aug,

doi = "10.1109/CSE/EUC.2019.00016",

language = "English",

series = "Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "36--39",

editor = "Meikang Qiu",

booktitle = "Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019",

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Aslam, A, Qamar, U, Khan, RA, Saqib, P, Ahmad, A & Qadeer, A 2019, Opinion mining using live Twitter data. in M Qiu (ed.), Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019., 8919578, Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 36-39, 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019, New York, United States, 1/08/19. https://doi.org/10.1109/CSE/EUC.2019.00016

Opinion mining using live Twitter data. / Aslam, Andleeb; Qamar, Usman; Khan, Reda Ayesha et al.
Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019. ed. / Meikang Qiu. Institute of Electrical and Electronics Engineers Inc., 2019. p. 36-39 8919578 (Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Opinion mining using live Twitter data

AU - Aslam, Andleeb

AU - Qamar, Usman

AU - Khan, Reda Ayesha

AU - Saqib, Pakizah

AU - Ahmad, Aleena

AU - Qadeer, Aiman

PY - 2019/8

Y1 - 2019/8

N2 - Opinion mining and extracting Sentiments of people is the need of today. This is the era of Big data. Because of social networking sites, it's easy to analyze sentiments of people. Sentiment analysis is a technique to extract opinions of people regarding any product, issue or personality. This paper is about extracting live twitter data regarding any topic and converting it into structured form from un-structured one. Opinions are extracted from the text data and polarity is assigned against each tweet. Polarity of data can be positive, negative or neutral. Most recent and popular opinions can be extracted. It is useful for both market analyzers as well as customers. Customers get to know honest reviews about any product and companies can know their customer's interests. Furthermore, predictions are also given based on the classified data.

AB - Opinion mining and extracting Sentiments of people is the need of today. This is the era of Big data. Because of social networking sites, it's easy to analyze sentiments of people. Sentiment analysis is a technique to extract opinions of people regarding any product, issue or personality. This paper is about extracting live twitter data regarding any topic and converting it into structured form from un-structured one. Opinions are extracted from the text data and polarity is assigned against each tweet. Polarity of data can be positive, negative or neutral. Most recent and popular opinions can be extracted. It is useful for both market analyzers as well as customers. Customers get to know honest reviews about any product and companies can know their customer's interests. Furthermore, predictions are also given based on the classified data.

KW - Opinion Mining

KW - Polarity

KW - Sentiment Analysis

KW - Twitter

KW - Twitter Data

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U2 - 10.1109/CSE/EUC.2019.00016

DO - 10.1109/CSE/EUC.2019.00016

M3 - Conference contribution

AN - SCOPUS:85077024128

T3 - Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019

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BT - Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019

A2 - Qiu, Meikang

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019

Y2 - 1 August 2019 through 3 August 2019

ER -

Aslam A, Qamar U, Khan RA, Saqib P, Ahmad A, Qadeer A. Opinion mining using live Twitter data. In Qiu M, editor, Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 36-39. 8919578. (Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019). doi: 10.1109/CSE/EUC.2019.00016

Opinion mining using live Twitter data

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this