Extraction of Data from OSN Using Aho- Corasick Algorithm
Keywords:
Artificial Intelligence, Machine Learning, Convolutional Neural Network, Event detection, Online Social Networks, affective analysis, natural language processing,Abstract
Online social networks (OSNs) are utilized by people to express their emotions and opinions on various topics. However, their behavior may vary depending on the nature of an occasion, its dissemination rate in OSNs, and specific locations. To address this issue, this study proposes an event recognition framework that identifies an event's occurrence based on changes in customers' behavior in OSNs. The framework can recognize events of any subject and serve a variety of functions. The proposed framework comprises four main modules: (1) customer location determination; (2) message extraction from OSNs; (3) subject identification using natural language processing (NLP) based on the Deep Belief Network (DBN); and (4) event analysis by customers using the suggested framework. Over the years, user behavior studies have been used to investigate the psychological underpinnings of activities in various fields. Recently, this research has been employed to track various types of occurrences and provide recommendations. An individual's behavior is influenced by a variety of factors, including their health and well-being. Similarly, the behavior of the general population can also be influenced by the state of their health. Online social networks are now a popular means of communicating thoughts, feelings, and actions. As a result, they provide an extensive amount of data that represents user behavior. However, analyzing user behavior can be a challenging task, which has led to the study of specific models to detect unusual user behavior. Research has focused on social media user behavior analysis in various contexts, including political events, different recommendation systems, public health, etc.
Downloads
References
O. Ajao, J. Hong, and W. Liu. A survey of location inference techniques on twitter. Journal of Information Science, 1:1–10, 2015.
E. Amig´ o, J. C. De Albornoz, I. Chugur, A. Corujo, J. Gonzalo, T. Mart´ın, E. Meij, M. De Rijke, and D. Spina. Overview of replab 2013: Evaluating online reputation monitoring systems. In Proceedings of CLEF, pages 333–352. Springer, 2013.
F. Atefeh and W. Khreich. A survey of techniques for event detection in twitter. Computational Intelligence, 31(1):132–164, 2015.
H. Bo, P. Cook, and T. Baldwin. Geolocation prediction in social media data by finding location indicative words. In Proceedings of COLING, pages 1045–1062, 2012.
J. Bollen, H. Mao, and A. Pepe. Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena. In Proceedings of ICWSM, pages 450–453, 2011.
J. D. Burger, J. Henderson, G. Kim, and G. Zarrella. Discriminating gender on twitter. In Proceedings of EMNLP, pages 1301–1309, 2011.
H.-w. Chang, D. Lee, M. Eltaher, and J. Lee. @ phillies tweeting from philly? predicting twitter user locations with spatial word usage. In Proceedings of ASONAM, pages 111–118, 2012.
Y. Chen, J. Zhao, X. Hu, X. Zhang, Z. Li, and T.-S. Chua. From interest to function: Location estimation in socialmedia. In Proceedings of AAAI, pages 180–186, 2013.
Z. Cheng, J. Caverlee, and K. Lee. You are where you tweet: a content-based approach to geo-locating twitter users. In Proceedings of CIKM, pages 759–768, 2010.
R. Compton, D. Jurgens, and D. Allen. Geotagging one hundred million twitter accounts with total variation minimization. In IEEE Big Data, pages 393–401, 2014.
M. Conover, J. Ratkiewicz, M. R. Francisco, B.Gonc¸alves, F. Menczer, and A. Flammini.Political polarizationon twitter.In Proceedings of ICWSM, pages 89–96, 2011.
M. D. Conover, B. Gonc¸alves, J. Ratkiewicz, A. Flammini, and F. Menczer. Predictingthe political alignment of twitter users. In IEEE PASSAT/SocialCom, pages 192–199,2011.
D. Doran, S. Gokhale, and A. Dagnino. Accurate local estimation of geo-coordinates for social media posts. arXiv preprint arXiv:1410.4616, 2014.
M. Dredze, M. Osborne, and P. Kambadur. Geolocation for twitter: Timing matters. InProceedings of NAACL-HLT, pages 1064–1069, San Diego, California, 2016.
Vinston Raja R., Prabu Sankar N., Neela Gandhi V., Angel Kiruba D. R., Detection of Covid-19 Cases from Chest X-Ray Images using CNN, DOI: https://doi.org/10.52783/jes.3271, Vol. 20 No. 6s (2024)
Vinston Raja R., Jimson L., Gnanaprakasam C., Jerrin Simla A., Sharmila J. L. B., Lincy Jemina S. Enhanced Brain Tumor Analysis: Integrating ResNet50 with Convolutional Block Attention Modules for Advanced Insights, DOI: https://doi.org/10.52783/jes.3272, Vol. 20 No. 6s (2024)
Vinston Raja R., D. . B., J. . L., A. K. . D. R., and G. . C., “Automatic Identification of Hurricane Damage Using a Transfer Learning Approach with Satellite Images”, Int J Intell Syst Appl Eng, vol. 12, no. 16s, pp. 389–399, Feb. 2024.
Kumar, Deepak A.Gnanaprakasam C.Sankar P.N.;Senthamilarasi N.Kumaran, Chenni J, Raja, Vinston R .Suseendra R. VULNERABILITY DETECTION IN SOFTWARE APPLICATIONS USING STATIC CODE ANALYSIS. Journal of Theoretical and Applied Information TechnologyVolume 102, Issue 4, Pages 1307 - 132029 February 2024,ISSN 19928645
Vinston Raja R, Deepak Kumar A, PrabuSankar N, Senthamilarasi N, Dr. ChenniKumaran J., Prediction and Distribution of Disease Using HybridClustering Algorithm in Big Data, International Journal on Recent and Innovation Trends in Computing and Communication, ISSN: 2321-8169 Volume: 11 Issue: 10,DOI: https://doi.org/10.17762/ijritcc.v11i10.8469
A. Deepak kumar, N.Revathi, S. IrinSherly, R. Lalitha, R. Vinston Raja., Innovative Time Series-Based Ecg Feature Extraction For Heart Disease Risk Assessment Journal of Theoretical and Applied Information Technology, 15th November 2023 -- Vol. 101. No. 21-- 2023
Vinston Raja R, Deepak Kumar A, PrabuSankar N, Chidambarathanu K, Thamarai I, Krishnaraj M, IrinSherly S., Comparative Evaluation Of Cardiovascular Disease Using MLR And RF Algorithm With Semantic Equivalence., Journal of Theoretical and Applied Information Technology.,30th September 2023 -- Vol. 101. No. 18-- 2023
PrabuSankar, N. Jayaram, R. IrinSherly, S. Gnanaprakasam, C. Vinston Raja, R. Study of ECG Analysis based Cardiac Disease Prediction using Deep Learning Techniques,International Journal of Intelligent Systems and Applications in Engineering, 2023, 11(4), pp. 431–438
Vinston Raja, R. and Ashok Kumar, K. ‘Financial Derivative Features Based Integrated Potential Fishing Zone (IPFZ) Future Forecast'. Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 3637-3649, 2023.
Vinston, R.R., Adithya, V., Hollioake, F.A., Kirran, P.L. Dhanalakshmi, G., Identification of Underwater Species Using Condition-Based Ensemble Supervised Learning Classification,International Journal of Intelligent Systems and Applications in Engineering, 2023, 11(3), pp. 1–12
R. Vinston Raja and K. Ashok Kumar, Fisher Scoring with Condition Based Ensemble Supervised Learning Classification Technique for Prediction in PFZ Journal of Uncertain Systems 2022 15:03
Vinston Raja, R., Ashok Kumar, K. ., &Gokula Krishnan, V. (2023). Condition based Ensemble Deep Learning and Machine Learning Classification Technique for Integrated Potential Fishing Zone Future Forecasting. International Journal on Recent and Innovation Trends in Computing and Communication, 11(2), 75–85. https://doi.org/10.17762/ijritcc.v11i2.6131
R. V. Raja and K. A. Kumar, "Collision Averting Approach in Deep Maritime Boats using Prophecy of Impact Direction," 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI),India, 2021, pp. 1066-1071,doi:10.1109/ICOEI51242.2021.9453084.
R. Vinston Raja, A. Deepak Kumar, DR. I. Thamarai, S. Noor mohammed, R. Rajesh Kanna, Analytic Approach of Predicting Employee Attrition Using Data Science Techniques, Journal of Theoretical and Applied Information Technology,15th May 2023 Vol. 101. No. 9- 2023
Rose, J.D., Vinston Raja, R, .Lakshmi, D. Saranya, S., Mohanaprakash, T.A. Privacy Preserving and Time Series Analysis of Medical Dataset using Deep Feature Selection, International Journal on Recent and Innovation Trends in Computing and Communication, 2023, 11(3), pp. 51–57
An AI Powered Threat Detector for Banking Sector Using Intelligent Surveillance Cameras, Kumar, A.D., Vinston Raja, R., Mithun, P. Arthiya, A.P., Bujitha, R.A. Proceedings of the 2nd IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023, 2023
Doss, S., Paranthaman, J., Raja, V.R., Anand, J.G, Similarity-Based Gene Duplication Prediction In Protein-Protein Interaction Using Deep Artificial Ecosystem Network, Journal of Theoretical and Applied Information Technologythis link is disabled, 2022, 100(18), pp. 5232–5246
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
