Open AccessMetoo Movement Analysis through the Lens of Social Media
Author(s) -
P. Asha*,
K. Sri Neeharika,
T. Sindhura
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c4432.098319
Subject(s) - variety (cybernetics) , sentiment analysis , computer science , task (project management) , domain (mathematical analysis) , social media , natural language processing , artificial intelligence , movement (music) , through the lens metering , data science , lens (geology) , world wide web , engineering , mathematical analysis , philosophy , mathematics , systems engineering , petroleum engineering , aesthetics
Sentiment analysis is an errand which is used to analyse people’s opinions which has been derived out of textual data seems productive for palpating various NLP applications. The grievances associated with this task is that, there prevails variety of sentiments within these documents, accompanied with diverse expressions. Therefore, it seems hard to whip out all sentiments employing a dictionary which is commonly used. This work attempts at constructing the domain sentiment dictionary, by employing the external textual data. Besides, various classification models could be utilised to classify the documents congruent to their opinion. We have also implemented topic modelling, emoticon analysis and optimized gender classification in our proposed system. Many sectors have been identified where women are being abused. Clusters are formed for these sectors and the most affected sector is also identified.