dc.contributor.advisor |
Ranathunga S |
|
dc.contributor.author |
Ameen AA |
|
dc.date.accessioned |
2022 |
|
dc.date.available |
2022 |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Ameen, A.A. (2022). Understanding the political opinion of Sri Lankans through deep learning based social media data analysis [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/21593 |
|
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/21593 |
|
dc.description.abstract |
With the rising popularity of social media usage, the data generated through it has
significantly increased. By focusing critically on these data, certain patterns, traits and
opinions can be obtained which can be used for the betterment of the society. This research
focuses on finding out the possibility of understanding the political opinion of the country
based on these social media data. Understanding the impact of these data will prompt the
public to use these platforms to a greater effect thus guiding the decision-makers to make
better and informed decisions.
To achieve the above objective English and Sinhala comments from 60 posts from six
prominent politicians in Sri Lanka were collected from November 2019 to December
2021. These data was then annotated as positive, negative or neutral sentiments.
6591 annotated comments were used to fine-tune the XLM-RoBERTa (XLM-R) pretrained
model
for
a
text
classification
task.
XLM-R
is
the
new
state-of-the-art
multilingual
masked
language model which performs exceptionally well in cross-lingual
understanding. To improve the performance of the baseline model a novel approach of
adding the context of the comment as a feature in the comment is proposed in the thesis.
The XLM-R baseline model achieved an F1 score of 79% while the model using
politicians' representation in parliament as a context obtained an F1 score of 91%. The
models performed exceptionally well for unseen data as well, when tested with data related
to politicians not considered in the training data, the model reported an F1 score of 86%.
Predicting the sentiments using the best model for the latest posts of the six main
politicians in the study, the current opinion of the people was derived. Based on it, the
Government representatives President Gotabaya Rajapaksha, Prime Minster Mahinda
Rajapaksha, and Former President Maithripala Sirisena obtained negative sentiments
while Opposition MPs Sajith Premadasa and Anura Kumara obtained positive sentiments. |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
POLITICAL OPINIONS – Sri Lanka |
en_US |
dc.subject |
DEEP LEARNING |
en_US |
dc.subject |
SOCIAL MEDIA DATA ANALYSIS |
en_US |
dc.subject |
COMPUTER SCIENCE & ENGINEERING -Dissertation |
en_US |
dc.subject |
COMPUTER SCIENCE -Dissertation |
en_US |
dc.subject |
INFORMATION TECHNOLOGY -Dissertation |
en_US |
dc.title |
Understanding the political opinion of Sri Lankans through deep learning based social media data analysis |
en_US |
dc.type |
Thesis-Abstract |
en_US |
dc.identifier.faculty |
Engineering |
en_US |
dc.identifier.degree |
MSc In Computer Science and Engineering |
en_US |
dc.identifier.department |
Department of Computer Science and Engineering |
en_US |
dc.date.accept |
2022 |
|
dc.identifier.accno |
TH4978 |
en_US |