Kernel Metadata Declaration — on demand

What the DOI identifies

Advancement in NLP with Decision Tree: The Impact of social media on Enhancing Women's Safety in Indian Cities

10.46243/jst.2023.v8.i12.pp195-207 · JournalArticle — an article in a journal · Digital · Visual · Language · en

Published 2023-12-12

Part of Journal of Science & Technology · ISSN 2456-5660 · vol. 8 · no. 12 · pp. 195–207

Principal agents

• C. Gazala Akhtari C. Gazala Akhtari (author → Author)
• Longman Publishers (publisher → Publisher)

Also in the record, outside the Kernel: the abstract, the licence, 4 links, 20 references. Source: Crossref (member 25296), registered 2024-02-16, last deposited 2026-09-17.

⬇ Record (JSON) ⬇ Declaration (XML)

System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1

Each element by the standard's name and the Handbook's (in grey), read off the record.

The record

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        "value": "Women and girls have been experiencing a lot of violence and harassment in public places in various cities starting from stalking and leading to sexual harassment or sexual assault. There have been several studies that have been conducted in cities across India and women report similar type of sexual harassment and passing off comments by other unknown people. The study that was conducted across most popular Metropolitan cities of India including Delhi, Mumbai, and Pune, it was shown that 60 % of the women feel unsafe while going out to work or while travelling in public transport. This work basically focuses on the role of social media in promoting the safety of women in Indian cities with special reference to the role of social media websites and applications including Twitter platform Facebook and Instagram. This work also focuses on how a sense of responsibility on part of Indian society can be developed the common Indian people so that they should focus on the safety of women surrounding them. Tweets on Twitter which usually contains images and text and also written messages and quotes which focus on the safety of women in Indian cities can be used to read a message amongst the Indian Youth Culture and educate people to take strict action and punish those who harass the women. Twitter and other Twitter handles which include hash tag messages that are widely spread across the whole globe sir as a platform for women to express their views about how they feel while they go out for work or travel in a public transport and what is the state of their mind when they are surrounded by unknown men and whether these women feel safe or not?",
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            "unstructured": "Barbosa, Luciano, and Junlan Feng. “Robust sentiment detection on twitter from biased and noisy data”, Proceedings of the 23rd international conference on computational linguistics: posters. Association for Computational Linguistics, 2010"
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            "doi": "10.1145/1871437.1871741",
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            "doi": "10.1109/icctict.2016.7514636",
            "unstructured": "N. Mamgain, E. Mehta, A. Mittal and G. Bhatt, “Sentiment analysis of top colleges in India using Twitter data”, 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), 2016, pp. 525-530, doi: 10.1109/ ICCTICT.2016.7514636"
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            "doi": "10.5120/ijca2017914022",
            "unstructured": "B. Gupta, M. Negi, K. Vishwakarma, G. Rawat, and P. Badhani (2017). “Study of Twitter sentiment analysis using machine learning algorithms on Python”. International Journal of Computer Applications, 165(9), 0975-8887"
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            "key": "ref8",
            "doi": "10.3390/ijerph15112537",
            "unstructured": "Reyes-Menendez, J. R. Saura, and C. Alvarez Alons. “Understanding# World Environment Day user opinions in Twitter: A topic-based sentiment analysis approach”. International Figure 7: Prediction results from test tweet. Figure 8: Sentiment graph performance measurement. DOI:https://doi.org/10.46243/jst.2023.v8.i12.pp195-207118 C. Gazala Akhtari, B. Vyhnavi, D. Deekshitha, Syed Sufiya Rana: Advancement in NLP with Decision Tree: The Impact of social media on Enhancing Women’s Safety in Indian Cities journal of environmental research and public health. 2018 Nov;15(11):2537"
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            "doi": "10.1109/aicai.2019.8701247",
            "unstructured": "D. Kumar and S. Aggarwal. “Analysis of Women Safety in Indian Cities Using Machine Learning on Tweets”, 2019 Amity International Conference on Artificial Intelligence (AICAI), 2019, pp. 159- 162, doi: 10.1109/AICAI.2019.8701247"
        },
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            "key": "ref10",
            "unstructured": "Vikram Chandra and Rampur Srinath. “Analysis of Women Safety using Machine Learning on Tweets”, (IRJET) 2020"
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            "key": "ref11",
            "unstructured": "F. Bravo-Marquez, B. Pfahringer, S. Mohammad and E. Frank, “Affective Tweets: a Weka Package for Analysing effect in Tweets”, Journal of Machine Learning Research, vol. 20, no. 92, pp. 1-6, 2020"
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            "key": "ref12",
            "doi": "10.1109/3ict51146.2020.9311990",
            "unstructured": "K. Abdul Sattar, Q. Obeidat and M. Akure. “Towards harnessing based learning algorithms for tweets sentiment analysis international conference of innovation and intelligence for informatics Computing and technology 2020”"
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            "doi": "10.1007/978-981-15-5397-4_51",
            "unstructured": "K. R. Teja, K. A. Kumar, G. S. Praveen and D. N. Harini. “Analysis of Crimes Against Women in India Using Machine Learning Techniques”, In Communication Software and Networks 2021 (pp. 499-510). Springer, Singapore"
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            "key": "ref14",
            "doi": "10.1007/978-3-030-90119-6_9",
            "unstructured": "Srinivasan, S., P. Muthu Kannan, and R. Kumar. “A Machine Learning Approach to Design and Develop a BEACON Device for Women’s Safety.” Recent Advances in Internet of Things and Machine Learning. Springer, Cham, 2022. 111-"
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            "doi": "10.1109/iceeict53079.2022.9768554",
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            "doi": "10.1109/icaccs54159.2022.9784981",
            "unstructured": "Ashok, K., et al. “A Survey on Design and Application Approaches in Women-Safety Systems.” 2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS). Vol. 1. IEEE, 2022"
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            "unstructured": "Tran, Martino, et al. “Monitoring the well-being of vulnerable transit riders using machine learning based sentiment analysis and social media: Lessons from COVID-19.” Environment and Planning B: Urban Analytics and City Science (2022): 23998083221104489"
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            "unstructured": "Islam, Md M., et al. “Risk factors identification and prediction of anemia among women in Bangladesh using machine learning techniques.” Current Women’s Health Reviews 18.1 (2022): 118-133"
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The Kernel Metadata Declaration

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