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Location-Wise News Headlines Classification and Sentiment Analysis: A Deep Learning Approach

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International Conference on Intelligent Computing and Smart Communication 2019

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

Text analysis has become the research interest for various researchers recently. Various text-related researches are being performed, of which text-based sentiment analysis is one. News headlines are the textual formatted data, which became the point of interest for various researchers for the purpose of text analysis. News headlines contain a long sequence of data so they can be used for various purposes. News headlines gives the information regarding what is currently going on but they give the overall situation. Our approach includes unique utilization of geospatial data-based technique to aggregate location-based news. This paper provides the novel approach of location-dependent news headlines classification and sentiment analysis over it using Deep Learning and clustering technique.

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References

  1. T.B. Shahi, A.K. Pant, Nepali news classification using Naïve-Bayes, support vector machines and neural networks. in 2018 International Conference on Communication, Information Computing Technology (ICCICT), Feb. 2–3, Mumbai, India

    Google Scholar 

  2. W. Jirasirilerd, P. Tangtisanon, Automatic labeling for Thai news articles based on vector representation of documents, in 2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST) (IEEE, 2018)

    Google Scholar 

  3. P. Kaushik, A.R. Sharma, Literature survey of statistical, deep and reinforcement learning in natural language processing. in International Conference on Computing, Communication and Automation (ICCCA 2017) (IEEE, 2017)

    Google Scholar 

  4. C. Li, G. Zhan, Z. Li, News text classification based on improved Bi-LSTM-CNN. in 2018 9th International Conference on Information Technology in Medicine and Education (ITME)

    Google Scholar 

  5. J. Zhang, Y. Li, J. Tian, T. Li, LSTM-CNN hybrid model for text classification. in 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

    Google Scholar 

  6. S. Sharma, J. Agrawal, S. Agrawal, S. Sharma, Machine Learning Techniques for Data Mining: A Survey (IEEE, 2013)

    Google Scholar 

  7. Z. Madhoushi, A.R. Hamdan, S. Zainudin, Sentiment analysis techniques in recent works, in Science and Information Conference 2015 (IEEE, 2015)

    Google Scholar 

  8. T.D. Bui, D.K. Nguyen, T.D. Ngo, Supervising an unsupervised neural network. in First Asian Conference on Intelligent Information and Database System (IEEE, 2009)

    Google Scholar 

  9. D. Cecchini, L. Na, Chinese news classification. in 2018 IEEE International Conference on Big Data and Smart Computing

    Google Scholar 

  10. U. Mohiuddin, H. Ahmed, M.A. Ismail, NEWSD: a real time news classification engine for web streaming data. in International Conference on Recent Advances in Computer Systems (RACS, 2015)

    Google Scholar 

  11. K. Gurmeet, B. Karan, News classification and its techniques: a review. IOSR J. Comput. Eng. (IOSR-JCE) 18(1) Ver. III (2016)

    Google Scholar 

  12. V. Rao, J. Sachdev, A machine learning approach to classify news articles based on location. in Proceedings of the International Conference on Intelligent Sustainable Systems (ICISS 2017)

    Google Scholar 

  13. J. Azzopardi, C. Staff, Fusion of news reports using surface-based methods. in 26th International Conference on Advanced Information Networking and Applications Workshops (2012)

    Google Scholar 

  14. J. Zhang, C.-T. Lu, M. Zhou, S. Xie, Y. Chang, P.S. Yu, HEER: heterogeneous graph embedding for emerging relation detection from news. in IEEE International Conference on Big Data (Big Data) (2016)

    Google Scholar 

  15. D. Nagalavi, M. Hanumanthappa, A new graph based sequence clustering approach for news article retrieval system. in IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI-2017)

    Google Scholar 

  16. M.W. UHL, Explaining U.S. consumer behavior with news sentiment. ACM Trans. Manag. Inf. Syst. 2, Article 9 (2011)

    Google Scholar 

  17. R. Mason, B. McInnis, S. Dalal, Machine learning for the automatic identification of terrorist incidents in Worldwide News Media. in 2012 IEEE, ISI 2012 June, 11–14, Washington D.C., USA

    Google Scholar 

  18. V. Bobichev, O. Kanishcheva, Sentiment analysis in the Ukrainian and Russian news. in 2017 IEEE First Ukraine Conference on Electrical and Computer Engineering (UKRCON)

    Google Scholar 

  19. B.S. Ko, C. Park, D. Lee, J. Kim, H.-J. Choi, D. Han, Finding news articles related to posts in social media: the need to consider emotion as a feature. in 2018 IEEE International conference on Big Data

    Google Scholar 

  20. G. Abali, E. Karaarslan, A. Hurriyetoglu, F. Dalkilic, Detecting Citizen problems and their locations using Twitter data. in 6th International Istanbul Smart Grids and Cities Congress and Fair (ICSG) (IEEE, 2018)

    Google Scholar 

  21. Nisha, P.J. Kaur, A Survey Of Clustering Techniques and Algorithm (IEEE, 2015)

    Google Scholar 

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Author information

Authors and Affiliations

  1. VJTI, Mumbai University, Mumbai, India

    Ashwin Kabra & Seema Shrawne

Authors
  1. Ashwin Kabra
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  2. Seema Shrawne
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Corresponding author

Correspondence to Seema Shrawne .

Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs, Gwalior, India

    Geetam Singh Tomar

  2. Indian Institute of Technology Indore, Indore, Madhya Pradesh, India

    Narendra S. Chaudhari

  3. Applied Computing Graduate Program, University of Vale do Rio dos Sinos, Sao Leopoldo, Rio Grande do Sul, Brazil

    Jorge Luis V. Barbosa

  4. Department of Electronics and Communication Engineering, THDC-Institute of Hydropower Engineering and Technology, Tehri, Uttarakhand, India

    Mahesh Kumar Aghwariya

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Cite this paper

Kabra, A., Shrawne, S. (2020). Location-Wise News Headlines Classification and Sentiment Analysis: A Deep Learning Approach. In: Singh Tomar, G., Chaudhari, N.S., Barbosa, J.L.V., Aghwariya, M.K. (eds) International Conference on Intelligent Computing and Smart Communication 2019. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0633-8_37

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