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Do Public and Government Think Similar About Indian Cleanliness Campaign?

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 898))

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Abstract

With the growth of internet, social networks has become primary source for people to present their views on different topics. The data collected from social media are considered enough as well as reliable to be processed and gather insights on the perceptions of people towards any topic. In this research work, an empirical study of the Twitter data (i.e. around 400,000 tweets) collected for the period of December 1, 2017 to March 31, 2018, pertaining to Indian Cleanliness Campaign called Swachh Bharat Abhiyan (SBA), which focuses on improving the cleanliness situation in the country, has been done. Here, a demographic distribution of the Twitter data has been generated by augmenting partial keyword matching along with Named Entity Recognition for geoparsing the tweets. This will help to study the involvement of the people in different areas of the country. Furthermore, Sentiment Analysis of the tweets has been performed to gather the perception of people towards the campaign. Also, to assure the integrity of the campaign, the tweets have been segregated into public and government generated tweets and the respective sentiments have been compared to determine the difference in perception of public and government in different areas of the country. This work can be considered of interest because there has not been any research work which focuses on analyzing the awareness and perception of people on SBA in detail.

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Notes

  1. 1.

    https://en.wikipedia.org/wiki/Administrative_divisions_of_India.

  2. 2.

    http://slusi.dacnet.nic.in/watershedatlas/list_of_state_abbreviation.htm.

  3. 3.

    POP: Population, LR: Avergae Literacy Rate, F_LR: Female Literacy Rate, PP: Public Posts percentage, PS: Public Sentiments, GS: Government Sentiments.

References

  1. Aramaki, E., Maskawa, S., Morita, M.: Twitter catches the flu: detecting influenza epidemics using Twitter. In: Proceedings of the Conference On Empirical Methods in Natural Language Processing, pp. 1568–1576. Association for Computational Linguistics (2011)

    Google Scholar 

  2. Culotta, A.: Towards detecting influenza epidemics by analyzing twitter messages. In: Proceedings of the First Workshop on Social Media Analytics, pp. 115–122. ACM (2010)

    Google Scholar 

  3. de Quincey, E., Kostkova, P.: Early warning and outbreak detection using social networking websites: the potential of Twitter. In: Kostkova, P. (ed.) eHealth 2009. LNICST, vol. 27, pp. 21–24. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-11745-9_4

    Chapter  Google Scholar 

  4. Fellbaum, C.: WordNet. Wiley Online Library (1998)

    Google Scholar 

  5. Gelernter, J., Mushegian, N.: Geo-parsing messages from microtext. Trans. GIS 15(6), 753–773 (2011)

    Article  Google Scholar 

  6. Ginsberg, J., Mohebbi, M.H., Patel, R.S., Brammer, L., Smolinski, M.S., Brilliant, L.: Detecting influenza epidemics using search engine query data. Nature 457(7232), 1012 (2009)

    Article  Google Scholar 

  7. New government policies and programmes, April 2018. https://powermin.nic.in/en/content/new-government-policies-and-programmes

  8. Lampos, V., Cristianini, N.: Tracking the flu pandemic by monitoring the social web. In: 2010 2nd International Workshop on Cognitive Information Processing (CIP), pp. 411–416. IEEE (2010)

    Google Scholar 

  9. Lampos, V., De Bie, T., Cristianini, N.: Flu detector - tracking epidemics on Twitter. In: Balcázar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds.) ECML PKDD 2010. LNCS (LNAI), vol. 6323, pp. 599–602. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15939-8_42

    Chapter  Google Scholar 

  10. Raj, S., Kajla, T.: Sentiment analysis of Swachh Bharat Abhiyan. Int. J. Bus. Anal. Intell. 3(1), 32 (2015)

    Google Scholar 

  11. Swachh Bharat Mission-Gramin, April 2018. http://swachhbharatmission.gov.in/sbmcms/index.htm

  12. Snow, J.: On the mode of communication of cholera. Edinb. Med. J. 1(7), 668 (1856)

    Google Scholar 

  13. Swachh Survekshan 2018, April 2018. https://www.swachhsurvekshan2018.org

  14. Tayal, D.K., Yadav, S.K.: Sentiment analysis on social campaign “Swachh Bharat Abhiyan” using unigram method. AI Soc. 32(4), 633–645 (2017)

    Article  Google Scholar 

  15. Wikipedia: Classification of Indian cities (2018). https://en.wikipedia.org/wiki/Classification_of_Indian_cities.htm

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Correspondence to Aarzoo Dhiman .

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Dhiman, A., Toshniwal, D. (2019). Do Public and Government Think Similar About Indian Cleanliness Campaign?. In: Lossio-Ventura, J., Muñante, D., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2018. Communications in Computer and Information Science, vol 898. Springer, Cham. https://doi.org/10.1007/978-3-030-11680-4_34

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  • DOI: https://doi.org/10.1007/978-3-030-11680-4_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11679-8

  • Online ISBN: 978-3-030-11680-4

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