Investigating Public Awareness of Air Pollution in Western Balkans by analyzing Tweets and News Article Teasers
Date Issued
2022
Author(s)
Madjar, Angela
Gjorshoska, Ivana
Prodanova, Jana
Dedinec, Aleksandra
Abstract
Air pollution is a serious threat to the health of
people living in Western Balkans, with the biomass being one of
the main pollutants. This study is based on the assumption that
air pollution escalation in Western Balkan countries during
winter will provoke a more intense activity on Twitter, while
acknowledging that people’s opinions and feelings can often be
influenced by content presented in news articles. The objective
of this study is to investigate public awareness of air pollution in
Macedonia, Serbia, Bosnia and Herzegovina and Montenegro.
Natural Language Processing techniques such as Sentiment
Analysis and Topic Modeling, as well as Statistical Analysis are
employed to determine whether Twitter discussions regarding
air pollution reflect the PM10 levels measured by official air
monitoring stations in these countries. Such analyses are also
performed on news article teasers, attempting to determine
whether mass media portrays a realistic ambient condition and
aims to promote pro-environmental behavior. The results of this
study suggest that using Correlation Analysis to check for
resemblance between the frequency of sentiments detected in
social media discussions and the temporal changes in the PM10
concentration in the air, can serve as a measure of public
awareness of air pollution. Analyzing the content of the tweets
can reveal issues in the public opinion and thus, contribute to
tackling them down.
people living in Western Balkans, with the biomass being one of
the main pollutants. This study is based on the assumption that
air pollution escalation in Western Balkan countries during
winter will provoke a more intense activity on Twitter, while
acknowledging that people’s opinions and feelings can often be
influenced by content presented in news articles. The objective
of this study is to investigate public awareness of air pollution in
Macedonia, Serbia, Bosnia and Herzegovina and Montenegro.
Natural Language Processing techniques such as Sentiment
Analysis and Topic Modeling, as well as Statistical Analysis are
employed to determine whether Twitter discussions regarding
air pollution reflect the PM10 levels measured by official air
monitoring stations in these countries. Such analyses are also
performed on news article teasers, attempting to determine
whether mass media portrays a realistic ambient condition and
aims to promote pro-environmental behavior. The results of this
study suggest that using Correlation Analysis to check for
resemblance between the frequency of sentiments detected in
social media discussions and the temporal changes in the PM10
concentration in the air, can serve as a measure of public
awareness of air pollution. Analyzing the content of the tweets
can reveal issues in the public opinion and thus, contribute to
tackling them down.
Subjects
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