Online networking is quickly getting to be one of the mediums of decision for understanding the social beat of an area. To survey this social beat it is basic to have an exact appraisal of who is saying what in web-based social networking. Fear monger bunches like al-quida, Indian mujahedeen, ISIS and other psychological oppressor bunches are spreading their purposeful publicity utilizing web or distinctive web-based social networking sites like Facebook, Twitter and Google+. Essential plan to stop or diminish spreading of psychological oppression is to expel these records. To execute this thought needs bunches of human endeavors which incorporate perusing part of data and dissecting contain. So to lessen human endeavors we will make a framework which recognize message given by fear based oppressor amass on twitter. Our framework will arrange tweets and discovers tweets are supporting ISIS gathering or not. We need to fabricate a framework which will give better outcome for analyzers.

Terrorism, ISIS, social media radical content, text mining, natural language processing, user cluster

[1] Ms. Pooja S. Kade1, Prof. N.M. Dhande, “ A Paper on Web Data Segmentation for Terrorism Detection using Named Entity Recognition Technique” presented at International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 – 0056, p-ISSN: 2395 – 0072,Volume: 04 Issue: 01 | Jan -2017,
[2] Budak Arpinar & Ugur Kursuncu and Dilshod Achilov, “Social Media Analytics to Identify and Counter Islamist Extremism: Systematic Detection, Evaluation, and Challenging of Extremist Narratives Online” presented at International Conference on Collaboration Technologies and Systems. 978 – 1 – 5090 – 2300 – 4 /16 2016 IEEE.
[3] Surajit Dasgupta, Chandan Prakash, “Intelligent Detection of Influential Nodes in Networks” presented at International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) , 978 – 1 – 4673 – 9939 – 5 /16, 2016-IEEE,
[4] Michael Ashcroft, Ali Fisher, Lisa Kaati, Enghin Omer, Nico Prucha, “Detecting Jihadist Messages on Twitter” presented at European Intelligence and Security Informatics Conference 978 – 1 – 4799 – 8657 – 6 /15, 2015 IEEE.
[5] Sonali Vighne, Priyanka Trimbake, Anjali Musmade, Ashwini Merukar, Sandip Pandit, “An Approach to Detect Terror Related Activities on Net” presented at IJARIIE-ISSN(O)-2395 – 4396, Vol-2 Issue-1 2016.
[6] Wei Wei Carnegie, Kenneth Joseph, Huan Liu, Kathleen M. Carley,” The Fragility of Twitter Social Networks Against Suspended Users” International Conference on Advances in Social Networks Analysis and Mining, 2015 ISBN: 978 – 1 – 4503 – 3854, 2015 IEEE/ACM.
[7] Sharath Kumar A and Sanjay Singh, ” Detection of User Cluster with Suspicious Activity in Online Social Networking Sites” Second International Conference on Advanced Computing, Networking and Security, 978 – 0 – 7695 – 5127 - 2/13,2013 IEEE
[8] Ala Berzinji, Frzand Sherko Abdullah, Ali Hayder kakei, “Analysis of Terrorist Groups on Facebook”, 978 – 0 – 7695 – 5062 – 6 /13, IEEE.