Article

Open Source Social Media Analytics for Intelligence and Security Informatics Applications

Authors:

Vikram GoyalAuthors Info & Claims

BDA 2015: Proceedings of the 4th International Conference on Big Data Analytics - Volume 9498

Pages 21 - 37

https://doi.org/10.1007/978-3-319-27057-9_2

Published: 15 December 2015 Publication History

Abstract

Open-Source Intelligence OSINT is intelligence collected and inferred from publicly available and overt sources of information. Open-Source social media intelligence is a sub-field within OSINT with a focus on extracting insights from publicly available data in Web 2.0 platforms like Twitter micro-blogging website, YouTube video-sharing website and Facebook social-networking website. In this paper, we present an overview of Intelligence and Security Informatics ISI applications in the domain of open-source social media intelligence. We present technical challenges and introduce basic Machine Learning based framework, tools and techniques within the context of open-source social media intelligence using two case-studies. The focus of the paper is on mining free-form textual content present in social media websites. In particular we describe two important application: online radicalization and civil unrest. In addition to covering basic concepts and applications, we discuss open research problem, important papers, publication venues, research results and future directions.

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Cited By

Kursuncu UGaur MCastillo CAlambo AThirunarayan KShalin VAchilov DArpinar ISheth A(2019)Modeling Islamist Extremist Communications on Social Media using Contextual DimensionsProceedings of the ACM on Human-Computer Interaction10.1145/33592533:CSCW(1-22)Online publication date: 7-Nov-2019
https://dl.acm.org/doi/10.1145/3359253
Agarwal S(2017)Open source social media intelligence for enabling government applicationsACM SIGWEB Newsletter10.1145/3110394.31103972017:Summer(1-19)Online publication date: 28-Jul-2017
https://dl.acm.org/doi/10.1145/3110394.3110397
Agarwal SSureka A(2017)Investigating the Role of Twitter in E-Governance by Extracting Information on Citizen Complaints and Grievances ReportsBig Data Analytics10.1007/978-3-319-72413-3_21(300-310)Online publication date: 12-Dec-2017
https://dl.acm.org/doi/10.1007/978-3-319-72413-3_21
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Information

Published In

cover image Guide Proceedings

BDA 2015: Proceedings of the 4th International Conference on Big Data Analytics - Volume 9498

December 2015

256 pages

ISBN:9783319270562

Editors:
Naveen Kumar
University of Delhi, Delhi, India
,
Vasudha Bhatnagar
University of Delhi, Delhi, India

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 15 December 2015

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Cited By

Kursuncu UGaur MCastillo CAlambo AThirunarayan KShalin VAchilov DArpinar ISheth A(2019)Modeling Islamist Extremist Communications on Social Media using Contextual DimensionsProceedings of the ACM on Human-Computer Interaction10.1145/33592533:CSCW(1-22)Online publication date: 7-Nov-2019
https://dl.acm.org/doi/10.1145/3359253
Agarwal S(2017)Open source social media intelligence for enabling government applicationsACM SIGWEB Newsletter10.1145/3110394.31103972017:Summer(1-19)Online publication date: 28-Jul-2017
https://dl.acm.org/doi/10.1145/3110394.3110397
Agarwal SSureka A(2017)Investigating the Role of Twitter in E-Governance by Extracting Information on Citizen Complaints and Grievances ReportsBig Data Analytics10.1007/978-3-319-72413-3_21(300-310)Online publication date: 12-Dec-2017
https://dl.acm.org/doi/10.1007/978-3-319-72413-3_21
Agarwal SSureka A(2017)A Collision of Beliefs13th International Conference on Distributed Computing and Internet Technology - Volume 1010910.1007/978-3-319-50472-8_4(43-57)Online publication date: 13-Jan-2017
https://dl.acm.org/doi/10.1007/978-3-319-50472-8_4
Agarwal SSureka AMarathe MMohania MMausam Jain P(2016)Investigating the Potential of Aggregated Tweets as Surrogate Data for Forecasting Civil ProtestsProceedings of the 3rd IKDD Conference on Data Science, 201610.1145/2888451.2888466(1-6)Online publication date: 13-Mar-2016
https://dl.acm.org/doi/10.1145/2888451.2888466

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