Comparative Study of Sentiment Analysis on Cyber Security Related Multi-sourced Data in Social Media Platforms

Keshav Kapur, Rajitha Harikrishnan, S. Raghavendra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The comparative study investigates cyber security attitudes and behaviour across time using data gathered from social networking platforms such as Reddit and Twitter. Due to the continuously advancing technology in the modern world, enormous amounts of data are produced every second. The chosen field of study seeks to determine the opinions of people on social media posts. The dataset for the proposed work was a multi-source dataset from the comment or post section of various social networking sites like Twitter, Reddit, etc. Natural Language Processing Techniques were incorporated to perform sentiment analysis on the obtained dataset. The proposed work provides a comparative analysis using various techniques namely ML, DL, and lexicon-based. Naive Bayes Classifier was used as a Machine Learning algorithm, TextBlob is used as the Lexicon-based approach, and the deep-learning algorithm used is BiLSTM. It was observed that BiLSTM model outperforms the other two models with an F1-score of 0.895, accuracy of 0.896, precision of 0.899, and recall of 0.891.

Original languageEnglish
Title of host publicationApplications and Techniques in Information Security - 13th International Conference, ATIS 2022, Revised Selected Papers
EditorsSrikanth Prabhu, Shiva Raj Pokhrel, Gang Li
PublisherSpringer Science and Business Media Deutschland GmbH
Pages88-97
Number of pages10
ISBN (Print)9789819922635
DOIs
Publication statusPublished - 2023
Event13th International Conference on Applications and Techniques in Information Security, ATIS 2022 - Manipal, India
Duration: 30-12-202231-12-2022

Publication series

NameCommunications in Computer and Information Science
Volume1804 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference13th International Conference on Applications and Techniques in Information Security, ATIS 2022
Country/TerritoryIndia
CityManipal
Period30-12-2231-12-22

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

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