Identifying key-players in online activist groups on Facebook social network
Online social media applications have become an integral part of our everyday life. Not only are they being utilised by individuals and legitimate businesses, but also recently several organised groups, such as activists, hactivists, and cybercriminals have adopted them to communicate and spread the...
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| Format: | Working paper |
| Sprache: | English |
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2015
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| _version_ | 1826297273891422208 |
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| author | Nouh, M |
| author_facet | Nouh, M |
| author_sort | Nouh, M |
| collection | OXFORD |
| description | Online social media applications have become an integral part of our everyday life. Not only are they being utilised by individuals and legitimate businesses, but also recently several organised groups, such as activists, hactivists, and cybercriminals have adopted them to communicate and spread their ideas. This represents a new source for intelligence gathering for law enforcement for instance, as it allows them an inside look at the behaviour of these previously closed, secretive groups. One possible opportunity with this online data source is to utilise the public exchange of social-media messages to identify key users in such groups. This is particularly important for law enforcement that wants to monitor or interrogate influential people in suspicious groups. In this paper, we utilise Social Network Analysis (SNA) techniques to understand the dynamics of the interaction between users in a Facebook-based activist group. Additionally, we aim to identify the most influential users in the group and infer their relationship strength. We incorporate sentiment analysis to identify users with clear positive and negative influences on the group; this could aid in facilitating a better understanding of the group. We also perform a temporal analysis to correlate online activities with relevant real-life events. Our results show that applying such data analysis techniques on users online behaviour is a powerful tool to predict levels of influence and relationship strength between group members. Finally, we validated our results against a ground truth and found that our approach is very promising at achieving its aims. |
| first_indexed | 2024-03-07T04:29:04Z |
| format | Working paper |
| id | oxford-uuid:cdaf309c-59b1-4b6d-9e6a-439a830e017c |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:29:04Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | oxford-uuid:cdaf309c-59b1-4b6d-9e6a-439a830e017c2022-03-27T07:30:19ZIdentifying key-players in online activist groups on Facebook social networkWorking paperhttp://purl.org/coar/resource_type/c_8042uuid:cdaf309c-59b1-4b6d-9e6a-439a830e017cCyber intelligence (Computer security)Computer securityEnglishORA Deposit2015Nouh, MOnline social media applications have become an integral part of our everyday life. Not only are they being utilised by individuals and legitimate businesses, but also recently several organised groups, such as activists, hactivists, and cybercriminals have adopted them to communicate and spread their ideas. This represents a new source for intelligence gathering for law enforcement for instance, as it allows them an inside look at the behaviour of these previously closed, secretive groups. One possible opportunity with this online data source is to utilise the public exchange of social-media messages to identify key users in such groups. This is particularly important for law enforcement that wants to monitor or interrogate influential people in suspicious groups. In this paper, we utilise Social Network Analysis (SNA) techniques to understand the dynamics of the interaction between users in a Facebook-based activist group. Additionally, we aim to identify the most influential users in the group and infer their relationship strength. We incorporate sentiment analysis to identify users with clear positive and negative influences on the group; this could aid in facilitating a better understanding of the group. We also perform a temporal analysis to correlate online activities with relevant real-life events. Our results show that applying such data analysis techniques on users online behaviour is a powerful tool to predict levels of influence and relationship strength between group members. Finally, we validated our results against a ground truth and found that our approach is very promising at achieving its aims. |
| spellingShingle | Cyber intelligence (Computer security) Computer security Nouh, M Identifying key-players in online activist groups on Facebook social network |
| title | Identifying key-players in online activist groups on Facebook social network |
| title_full | Identifying key-players in online activist groups on Facebook social network |
| title_fullStr | Identifying key-players in online activist groups on Facebook social network |
| title_full_unstemmed | Identifying key-players in online activist groups on Facebook social network |
| title_short | Identifying key-players in online activist groups on Facebook social network |
| title_sort | identifying key players in online activist groups on facebook social network |
| topic | Cyber intelligence (Computer security) Computer security |
| work_keys_str_mv | AT nouhm identifyingkeyplayersinonlineactivistgroupsonfacebooksocialnetwork |