eprintid: 4540
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/45/40
datestamp: 2023-11-09 16:16:13
lastmod: 2023-11-09 16:16:13
status_changed: 2023-11-09 15:58:39
type: conference_item
metadata_visibility: show
creators_name: Sarlan, A.
creators_name: Nadam, C.
creators_name: Basri, S.
title: Twitter sentiment analysis
ispublished: pub
keywords: Application programs; Computer operating systems; Data mining; Sales; Social networking (online), Customer perspectives; Language processing; Market place; Natural language processing; Natural languages; Opinion mining; Sentiment; Sentiment analysis; Social media; Twitter, Sentiment analysis
note: cited By 85; Conference of 6th International Conference on Information Technology and Multimedia, ICIMU 2014 ; Conference Date: 18 November 2014 Through 20 November 2014; Conference Code:111721
abstract: Social media have received more attention nowadays. Public and private opinion about a wide variety of subjects are expressed and spread continually via numerous social media. Twitter is one of the social media that is gaining popularity. Twitter offers organizations a fast and effective way to analyze customers' perspectives toward the critical to success in the market place. Developing a program for sentiment analysis is an approach to be used to computationally measure customers' perceptions. This paper reports on the design of a sentiment analysis, extracting a vast amount of tweets. Prototyping is used in this development. Results classify customers' perspective via tweets into positive and negative, which is represented in a pie chart and html page. However, the program has planned to develop on a web application system, but due to limitation of Django which can be worked on a Linux server or LAMP, for further this approach need to be done. © 2014 IEEE.
date: 2014
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937485143&doi=10.1109%2fICIMU.2014.7066632&partnerID=40&md5=8e309c5e50fab09f271fd4bb07531a01
id_number: 10.1109/ICIMU.2014.7066632
full_text_status: none
publication: Conference Proceedings - 6th International Conference on Information Technology and Multimedia at UNITEN: Cultivating Creativity and Enabling Technology Through the Internet of Things, ICIMU 2014
pagerange: 212-216
refereed: TRUE
isbn: 9781479954230
citation:   Sarlan, A. and Nadam, C. and Basri, S.  (2014) Twitter sentiment analysis.  In: UNSPECIFIED.