eprintid: 11858
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/18/58
datestamp: 2023-11-10 03:26:24
lastmod: 2023-11-10 03:26:24
status_changed: 2023-11-10 01:16:19
type: article
metadata_visibility: show
creators_name: Balakrishnan, V.
creators_name: Govindan, V.
creators_name: Arshad, N.I.
creators_name: Shuib, L.
creators_name: Cachia, E.
title: Facebook User Reactions And Emotion: An Analysis Of Their Relationships Among The Online Diabetes Community
ispublished: pub
note: cited By 2
abstract: With the advent of Web 2.0 technologies such as social media, online text sources provide large scale data repositories out of which valuable knowledge about human emotions can be derived. This paper aims to (i) detect and classify emotions of the Facebook diabetes community, (ii) examine the relationship of emotion and Facebook reactions, and (iii) identify user reaction predictors for each of the emotion. A total of 15K posts were randomly selected from several official Facebook diabetes support groups. Pre-processing was administered, resulting in 2475 Facebook posts for further analysis in this study. Emotion detection was first administered using Indico API, with results revealing anger, sadness and fear to be the top most emotions experienced, whilst love and wow emerged as the highest-ranking reactions. Precision and recall indicate the performance of the emotion detection mechanism ranged between 65 � 82 for all the emotions, compared to the human annotation. The average F-score recorded was 78. Both love and wow were found to significantly predict joy and fear, whereas angry was found to predict anger. The findings indicate that human emotions can be effectively detected based on users� textual communication, and significant relationships exists between several reactions and emotions © 2021,Malaysian Journal of Computer Science. All rights reserved
date: 2019
publisher: Faculty of Computer Science and Information Technology
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100495499&doi=10.22452%2fmjcs.sp2019no3.6&partnerID=40&md5=944dca5c23e0ca929fd5e6bec1a3cdea
id_number: 10.22452/mjcs.sp2019no3.6
full_text_status: none
publication: Malaysian Journal of Computer Science
volume: 2019
number: Specia
pagerange: 87-97
refereed: TRUE
issn: 01279084
citation:   Balakrishnan, V. and Govindan, V. and Arshad, N.I. and Shuib, L. and Cachia, E.  (2019) Facebook User Reactions And Emotion: An Analysis Of Their Relationships Among The Online Diabetes Community.  Malaysian Journal of Computer Science, 2019 (Specia).  pp. 87-97.  ISSN 01279084