Profiles Matching in Social Networks Based on Semantic Similarities and Common Relationships

Choumane, Ali; Ibrahim, Zein Al Abidin; Chebaro, Bilal

doi:10.1145/3093241.3093258

Cited by 6 publications

(5 citation statements)

References 8 publications

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“…Outros propuseram uma estrutura para agrupar usuários semelhantes a fim de formar uma comunidade visando a "identificar, extrair e caracterizar componentes proeminentes de tópicos e opiniões que as pessoas compartilham...", neste caso, "...durante eventos de crise no Twitter" [Gupta et al 2012]. Há outros, por exemplo, que visavam à recomendac ¸ão de amizade baseada na correspondência de perfis [Choumane et al 2017] e ainda outros que utilizaram entrevistas com intuito de verificarem a perspectiva de uma parcela específica de usuários [Brough et al 2020]. Todos estes casos trazem, de algum modo, um processo de identificac ¸ão e caracterizac ¸ão do usuário do Twitter que, no entanto, não corresponde diretamente ao objetivo deste estudo.…”

Section: Pesquisas Relacionadasunclassified

Mapeamento Sistemático da Literatura sobre a Caracterização do Usuário do Twitter

Oliveira,

Santos,

Mota

2023

Anais Do XIV Workshop Sobre Aspectos Da Interação Humano-Computador Na Web Social (WAIHCWS 2023)

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As redes sociais possuem um vasto conjunto de dados dos seus usuários. Coletar estes dados, transformá-los em informação e, posteriormente, em conhecimento, tem importância ímpar, não apenas para as empresas proprietárias destas redes mas para todo o “ecossistema”nestas redes. Este artigo apresenta um mapeamento sistemático da literatura e teve por objetivo encontrar uma resposta para o seguinte questionamento: quem é o usuário do twitter? Os artigos foram coletados das bases ACM Digital Library, Science Direct e IEEE Xplorer, conforme string definida, utilizando o método de busca automática. Dos artigos selecionados, foram retiradas 8 categorias de identificação de usuários: indivíduo ou organização, multirredes, malicioso, saúde, comportamento, demografia, interesses e identidade. Também a literatura cinzenta foi consultada para integrar o resultado a respeito do usuário do Twitter e gerou informações como a quantidade de usuários por gênero e os países com mais usuários do Twitter.

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Section: Pesquisas Relacionadasunclassified

Mapeamento Sistemático da Literatura sobre a Caracterização do Usuário do Twitter

Oliveira,

Santos,

Mota

2023

Anais Do XIV Workshop Sobre Aspectos Da Interação Humano-Computador Na Web Social (WAIHCWS 2023)

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“…User Behaviour: On another line of research, the authors in [14] [15] look at the profile and behavioural patterns of a user and discussed existing challenges on different OSNs. By integrating semantic similarity and existing relationships between users, it is possible to match profiles across various OSNs [16] [17]. Also, [18] conducted a detailed investigation of user profiles and proposed a matching scheme.…”

Section: Related Workmentioning

confidence: 99%

“…Besides, both sports star and politician have the same rate of negative comments. This is an example of positive comment in politicians (Table II, row [3]): "You are my president and I love you forever", and this is an example of negative in sports star (Table II, row [16]): "kill ur self". Duplication of comments.…”

Section: What Content Do Impersonator Publish?mentioning

confidence: 99%

How Impersonators Exploit Instagram to Generate Fake Engagement?

Zarei¹,

Farahbakhsh²,

Crespi³

2020

Preprint

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Impersonators on Online Social Networks such as Instagram are playing an important role in the propagation of the content. These entities are the type of nefarious fake accounts that intend to disguise a legitimate account by making similar profiles. In addition to having impersonated profiles, we observed a considerable engagement from these entities to the published posts of verified accounts. Toward that end, we concentrate on the engagement of impersonators in terms of active and passive engagements which is studied in three major communities including "Politician", "News agency", and "Sports star" on Instagram. Inside each community, four verified accounts have been selected. Based on implemented approach in our previous studies [1], we have collected 4.8K comments, and 2.6K likes across 566 posts created from 3.8K impersonators during 7 months. Our study shed light into this interesting phenomena and provides a surprising observation that can help us to understand better how impersonators engaging themselves inside Instagram in terms of writing Comments and leaving Likes.

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“…User Behaviour: On another line of research, the authors in [11] [12] look at the profile and behavioural patterns of a user and discussed existing challenges on different OSNs. By integrating semantic similarity and existing relationships between users, it is possible to match profiles across various OSNs [13] [14]. Also, [15] conducted a detailed investigation of user profiles and proposed a matching scheme.…”

Section: Related Workmentioning

confidence: 99%

Typification of Impersonated Accounts on Instagram

Zarei

Farahbakhsh

Crespi

2019

2019 IEEE 38th International Performance Computing and Communications Conference (IPCCC)

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Fake accounts and Impersonators on Online Social Networks such as Instagram are turning difficulties for society. This has attended to an increasing interest in detecting fake profiles and investigating their behaviours. Questions like who are impersonators? what are their characteristics? and are they bots? will arise. To answer, we begin this research by collecting data from three important communities on Instagram including "Politician", "News agency", and "Sports star". Inside each community, four verified top accounts are picked. Based on the users who reacted to their published posts, we detect 4K impersonators [1]. Then we employed well-known clustering methods to distribute impersonators into separated clusters to observe obscure behaviours and unusual profile characteristics. We also studied the cross-group analysis of clusters inside each community to explore engagements. Finally, we conclude the study by providing a complete investigation of the bot-like cluster.

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Profiles Matching in Social Networks Based on Semantic Similarities and Common Relationships

Cited by 6 publications

References 8 publications

Mapeamento Sistemático da Literatura sobre a Caracterização do Usuário do Twitter

Mapeamento Sistemático da Literatura sobre a Caracterização do Usuário do Twitter

How Impersonators Exploit Instagram to Generate Fake Engagement?

Typification of Impersonated Accounts on Instagram

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