Safety Measures Against Women Violence in India using Sentimental Analysis
S. Ramamoorthy1, R. Poorvadevi2
1Dr. S. Ramamoorthy, Associate Professor, Department of Computer Science Engineering, SRM Institute of Science and Technology, Kanchipuram, India.
2Dr. R. Poorvadevi, Assistant Professor, Department of Computer Science Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University, Kanchipuram, India.
Manuscript received on 05 April 2019 | Revised Manuscript received on 14 April 2019 | Manuscript Published on 24 May 2019 | PP: 150-154 | Volume-8 Issue-6S3 April 2019 | Retrieval Number: F10270486S319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Women status in the society gone through many changes from the Ancient days to modern society and they are promoted to equal status with man in many aspects by the reformers. Women in India facing many problems by the modern day society. Sharing 33% of equal responsibility in the social contribution, they are still living in the restless life. Increasing number of Violence and Crime rate against woman in India will set many unanswered questions to government and the society regarding women safety. The proposed work designed to analyze the various forms of violence and threats against the woman by making use of most popular and powerful social media data. The number of likes, tweets, comments, blogs and post on the particular incident against woman can be used for this analysis. These Social networking sites collectively update the feedback about particular incident and it will be exhibit under the discussion of many people. This will give the global picture of various crimes against woman and showcase how the intention framed and motivation behind the scenario. This data would helpful to safeguard the woman from the unlikely violence against them in the society. The model uses Sentimental analysis with machine learning technique and K-means clustering algorithm to classify the datasets. This model would recommend various guidelines and precautionary efforts needs to establish by the government and public awareness to save the woman from the various violence in the form of sexual harassments. This model also takes advantage to alert the woman from the difficult situations.
Keywords: Women Safety, Violence, Social Network Sites, Sentimental Analytics, Neural Tensor Networks etc.
Scope of the Article: Computer Science and Its Applications