Crowd Management using Sentiment Analysis

Authors(2) :-Prajaktee S. Rane, Rubeena A. Khan

Today, many users are using Social networking sites such as Facebook, Twitter, LinkedIn etc. where user's give their own opinion on particular event or specific situation. This paper focus on Crowd management and control using sentiment analysis. Congestion in crowded area is identified is noted through public opinions made on social networking sites. The public opinions are ambiguous and it is hard to analyse the situation manually or through simple algorithms. Peoples post their feeling through Twitter, LinkedIn etc. Their response for a specific situation is either positive, negative or neutral. The public opinions are then collected, processed and analysed using data mining techniques. In this paper, Sentiment analysis is done by rule-based algorithm. By analysis crowded area, we can move crowd to uncrowded area to avoid undesirable situation.

Authors and Affiliations

Prajaktee S. Rane
Department of Computer Engineering, Modern Education Society's College of Engineering, Pune, Maharastra, India
Rubeena A. Khan
Department of Computer Engineering, Modern Education Society's College of Engineering, Pune, Maharastra, India

Crowd Management, Sentiment Analysis, Rule-Based Algorithm.

  1. Yuichi Kawamoto, Naoto Yamada, Hiroki Nishiyama, Nei Kato, Yoshitaka Shimizu, Yao Zheng [1] presented “A Feedback Control Based Crowd Dynamics Management in IoT System”. DOI 10.1109/JIOT, IEEE, Internet of Things Journal, 2017
  2. Jianping Cao, Ke Zeng, Hui Wang, Member, Jiajun Cheng, Fengcai Qiao, Ding Wen, and Yanqing Gao “Web-Based Traf?c Sentiment Analysis - Methods and Applications” IEEE Transaction on Intelligent Transprtation Systems, VOL. 15, NO. 2, APRIL 2014 pp-844-853
  3. A Survey of Opinion Mining and Sentiment Analysis-Bing Liu, Lei Zhang, University of Illinois at Chicago, Chicago- C. C. Aggarwal and C. X. Zhai (eds.), Mining Text Data, DOI 10.1007/978-1-4614-3223-4_13, Springer Science+Business Media, LLC 2012 415-462
  4. A. Mantejo-Raez, M.C.Diaz-Galiano, L. A. Urena-Lopez and F. Martinz-Santiago “Crowd Explicit Sentiment Analysis”, Elsevier, Knowledge-Based Systems 69 (2014) 134-139
  5. Sasan Amini, Ilias Gerostathopoulos and Christian Prehofer “Big Data Analytics Architecture for Real-Time Traffic Control”, Models and Technologies for Intelligent Transoportation Systems (MT-ITS) 5th IEEE Internationa Conference, Augast 2017
  6. Eleonora D’Andrea, Pietro Ducange, Beatrice Lazzerini, and Francesco Marcelloni “Real-Time Detection of Traf?c From Twitter Stream Analysis”, IEEE Trasactions on Intelligent Transportation Systems, 2015
  7. Mr. Penubaka Balaji, Dr. O. Nagaraju, Prof.D. Haritha. “Levels of Sentiment Analysis and Its challenges: A Literature Review”. International Conference On Big Dta Analytics and Computational Intelligence, IEEE 2017 436-439
  8. Daniel Ansari “Sentiment Polarity Classification using Structural Features”, IEEE 15 th International Conference on Data Mininng Workshops,2015 pp-1270-1273
  9. Long Chenga, Jianwei Niua, Linghe Kongb, Chengwen Luoc, Yu Gu d, Wenbo Hee, Sajal K. Dasf “Compressive sensing based data quality improvement for crowd-sensing applications”, Elsevier, Journal of Network and Computer Applications, 77 (2017), 123-134
  10. Tanzim Mahmud, K. M. Azharul Hasan, Mahtab Ahmed, Thwoi Hla Ching Chak, “A rule based Approach for NLP based query Processing”, Electrical Information and Communication Technology (EICT), IEEE, Jan 2016, (78-82)
  11. Michel Wiegand, Manfread Klenner, Dietrich Klakow, “Bootstrapping Polarity Classi?ers with Rule-based Classi?cation”, Springer, December 2013, Volume 47, Issue 4, pp 1049-1088.
  12. David Milne, Ian H. Witten, “An Opensource Toolkit for mining `Wikipedia”, Elsevier, An Artificial Intelligence 294 (2013), 222-239
  13. Yisheng Lv, Yuanyuan Chen, Xiqiao Zhang, Yanjie Duan, and Naiqiang Li, “Social Media Based Transportation Research: the State of the Work and the Networking,” IEEE/CAA Journal of Automatica Sinica, Vol. 4, No. 1, January 2017
  14. Xinhu Zheng, Wei Chen, Pu Wang, Dayong Shen, SonghangChen, Xiao Wang, Qingpeng Zhang,and Liuqing Yang, “Big Data for Social Transportation”, IEEE Transactions on Intelliegent Transportation Systems, Vol 17, No. 3., March 2016.
  16. Geetika Gautam, Divakar yadav “Sentiment Analysis of Twitter Data Using Machine Learning Approaches and Semantic Analysis”, IEEE, 2014
  17. Alvaro Ortigosa, Jose Martin, Rosa M. Carro “Sentiment Analysis in Facebook and its application ine-learning”, Ortigosa et al./Computers in Human Behavior, Elsevier, 2013

Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 01-06
Manuscript Number : CSEIT18313
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Prajaktee S. Rane, Rubeena A. Khan, "Crowd Management using Sentiment Analysis", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.01-06, January-February.2018

Follow Us

Contact Us