Combining Entity Matching Techniques for Detecting Extremist Behavior on Discussion Boards

Dahlin, Johan; Johansson, Fredrik; Kaati, Lisa; Mårtenson, Christian; Svenson, Pontus

doi:10.1109/asonam.2012.154

Cited by 15 publications

(8 citation statements)

References 11 publications

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“…If a user is active on a number of web sites, forums, or other kinds of social media and uses several different aliases, alias matching can be very difficult. In [29] and [9], techniques for detecting multiple aliases in discussion boards are described. Some of the components that can be used to detect multiple aliases are: http://www.security-informatics.com/content/2/1/11…”

Section: Alias Matchingmentioning

confidence: 99%

Harvesting and analysis of weak signals for detecting lone wolf terrorists

et al. 2013

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Lone wolf terrorists pose a large threat to modern society. The current ability to identify and stop these kinds of terrorists before they commit a terror act is limited since they are hard to detect using traditional methods. However, these individuals often make use of Internet to spread their beliefs and opinions, and to obtain information and knowledge to plan an attack. Therefore there is a good possibility that they leave digital traces in the form of weak signals that can be gathered, fused, and analyzed. In this article we present an analysis method that can be used to analyze extremist forums to detect digital traces of possible lone wolf terrorists. This method is conceptually demonstrated using the FOI Impactorium fusion platform. We also present a number of different technologies which can be used to harvest and analyze pieces of information from Internet that may serve as weak digital traces that can be fused using the suggested analysis method in order to discover possible lone wolf terrorists.

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Section: Alias Matchingmentioning

confidence: 99%

Harvesting and analysis of weak signals for detecting lone wolf terrorists

et al. 2013

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“…The work in [35] which is followed by [18] is very relevant to our technique of Radicalization Index assignment to users. These works too deal with the recovery of radical signals from the online posts of social media users and thereby identify individuals as potential 'lone wolf terrorists'.…”

Section: Related Workmentioning

confidence: 99%

“…However, we also have used the technique of application of keyword analysis and crawling of web-sites of well-known radical/ counter radical organizations of Indonesia as discussed in later sections. Furthermore, [35] and [18] do not deal with location profiling of users which is one of the two major goals of our work. Fig.…”

Section: Related Workmentioning

confidence: 99%

Spatio-temporal Signal Recovery from Political Tweets in Indonesia

Mazumder

Das

Kim

et al. 2013

2013 International Conference on Social Computing

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Abstract-Online social network community now provides an enormous volume of data for analyzing human sentiment about people, places, events and political activities. It is increasingly clear that analysis of such data can provide great insights on the social, political and cultural aspect of the participants of these networks. As part of the Minerva project, currently underway at Arizona State University, we have analyzed a large volume of Twitter data to understand radical political activity in the provinces of Indonesia. Based on analysis of radical/counter radical sentiments expressed in tweets by Twitter users, we create a Heat Map of Indonesia which visually demonstrates the degree of radical activities in various provinces of Indonesia. We create the Heat Map of Indonesia by computing (i) the Radicalization Index and (ii) the Location Index of each Twitter user from Indonesia, who has expressed some radical sentiment in her tweets. The conclusions derived from our analysis matches significantly with the analysis of Wahid Institute, a leading political think tank of Indonesia, thus validating our results.

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“…The accuracy of this method has been improved, but not experimental results have been given. Johansson et al [9] draw on the framework of the paper [8], it has been improved and realized, and get better results, but the [9] does not take into account the same real people in different platforms released contents topic factors. We have made further expansion work on the basis of the work [9].…”

Section: Related Workmentioning

confidence: 99%

“…Nie et al [11] regards that the user's core interests will not be changed wiht the platform to change, they put forward a method of identity recognition by comparing the user's preferences. Dahlin et al [8] present a method of combing the output results of the field matching, graph matching and the matching technology based on text. The accuracy of this method has been improved, but not experimental results have been given.…”

Section: Related Workmentioning

confidence: 99%

Users Connection across Social Media Sites Based On Users'Relationship Vector

Zhou¹,

Li²,

Wei³

et al. 2017

Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)

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Abstract.The identification and association of multiple identities in different online social networks (osns) is an important problem, and also is the basis for many applications. At present, most of technologies try to solve this problem by matching the username of social networks or calculating the similarity of a pair of users' personal information from different platforms. However, due to the anonymity of social networks, these methods often fail to identify and associate multiple virtual identities. In this paper, we propose a classification method based on machine learning. Our method jointly consider the time, the text and the topic of the similarity to construct the feature vector to characterize the user's relationship. And we use the feature vectors to train the classifier. The model is evaluated on real world dataset, the twitter and sina weibo. The experimental results show that our method is effective.

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Combining Entity Matching Techniques for Detecting Extremist Behavior on Discussion Boards

Cited by 15 publications

References 11 publications

Harvesting and analysis of weak signals for detecting lone wolf terrorists

Harvesting and analysis of weak signals for detecting lone wolf terrorists

Spatio-temporal Signal Recovery from Political Tweets in Indonesia

Users Connection across Social Media Sites Based On Users'Relationship Vector

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