Human behavior analysis of BBC-news comments posted on facebook using lexicon-rule based approach

Title

Human behavior analysis of BBC-news comments posted on facebook using lexicon-rule based approach

Creator

Mathew C.; Sivakumar R.

Description

Today people spend a considerable part of their time on online platforms say, social media than with the real world. Social media, particularly Facebook is the platform for the users to post, share, like, tag and comment any photos and videos. This paper deals with the Facebook platform to study the human behavior based on the comments of five posts from BBC-news Facebook page. For every post in Facebook we can get different opinion or emotional behavior by different users. The behavior of people to the same event need not be similar, they can be different. A response through comments and smileys for a post portrays behaviors of people. Here the behavior analysis is performed on comments of the BBC news Facebook posts. The comments of the post are fetched by the online extractor named Socialfy [12]. This paper considered five news from unique from BBC-news Facebook page. The human behavior analysis performed using Python VADER (Valence Aware Dictionary and Sentiment Reasoner) package. This work uses the Lexicon approach to assign scores for the words and rule-based approach used to find the polarity type of words. The polarity of a post is the sentimental behavior of the people towards the post. The total polarity of this work tends towards neutral so, we could conclude that for each situation behavior of man can take positive or negative poles. 2019, Institute of Advanced Scientific Research, Inc. All rights reserved.

Source

Journal of Advanced Research in Dynamical and Control Systems, Vol-11, No. 6 Special Issue, pp. 1648-1655.

Date

2019-01-01

Publisher

Institute of Advanced Scientific Research, Inc.

Subject

Facebook; Human behavior analysis; Lexicon-rule based analysis; Polarity; Socialfy; VADER

Coverage

Mathew C., Department of Computer Science, CHRIST (Deemed to be University, Bengaluru, India; Sivakumar R., Department of Computer Science, CHRIST (Deemed to be University, Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 1943023X

Format

Online

Language

English

Type

Article

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074214570&partnerID=40&md5=8ec5dc61cd5e7125020fea3676a11f0c