Page 159 - C:\Users\am_se\OneDrive - Higher Education Commission\Desktop\FlipBook\

International Conference on

Recent Trends in Environmental Sustainability

ESCON22/FWSH/36
Social media analytics of public attitude towards environmental sustainability: a deep
learning approach

1
1
1,2
2
Tajamal Amin , Arslan Ali Raza , Asad Habib , Zahid Anwar and Sohaib Ahmad 1
1 Computer Science Department, COMSATS University Islamabad (CUI), Vehari Campus,
Vehari
2 Institute of Computing, Kohat University of Science & Information Technology (KUST),
Kohat. 26000, Pakistan
Correspondence: tajammalamin27@gmail.com

Abstract

The advent of web enabled technologies has given birth to novel research problems. Online
publishers are sharing their views, opinions, sentiments, suggestions and consumers’ choices.
A huge volume of opinionative contents is available about sustainable environment and its
economical perspectives as well as social dimensions. So far, public opinions regarding
environmental sustainability and its social and economic impacts are assessed mostly with self-
reported methods such as surveys, interviews and questionnaires but these methods have many
intrinsic limitations. To address all these limitations a more optimized and novel way of social
media analytics has been introduced in which users’ opinion shared on social networking
websites has been observed to get insights of target domains. A deep learning based algorithm
BERT (Bidirectional Encoder Representations from Transformers) is utilized for the semantic
orientation of tweets in order to assess the public attitudes towards sustainable environment
with respect to its social and economic perspectives. A new viewpoint on public attitudes’
toward environmental sustainability has been explored and reported to dig out the recent trends
in this field. BERT model proved as prominent method in extracting and evaluating public
opinions in big data analyses.
Keywords: Big Data, Deep Learning, Environmental Sustainability, Natural Language Processing,
Sentiment Analysis

Department of Environmental Sciences, COMSATS University Islamabad, Vehari Campus

126