scholarly journals Topic Modeling based on Louvain method in Online Social Networks

2016 ◽  
Author(s):  
Guilherme Sakaji Kido ◽  
Rodrigo Augusto Igawa ◽  
Sylvio Barbon Jr.
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Topic Modeling ◽  
Textual Content

Online Social Networks (OSNs) are the most used media nowadays, such as Twitter. The OSNs provide valuable information to marketing and competitiveness based on users posts and opinions stored inside huge volume of data from several themes, topics and subjects. In order to mining the topics discussed on an OSN we present a novel application of Louvain method for Topic Modeling based on communities detection in graphs by modularity. The proposed approach succeeded in finding topics in five different datasets composed of textual content from Twitter and Youtube. Another important contribution achieved was about the presence of texts posted by spammers. In this case, a particular behavior observed by graph architecture (density and degree) allows the classification of a topic as natural or artificial, this last created by the spammers on OSNs.

scholarly journals Artificial and Natural Topic Detection in Online Social Networks

2017 ◽  
Vol 10 (1) ◽  
pp. 80-98
Author(s):  
Sylvio Barbon Jr ◽  
Gabriel Marques Tavares ◽  
Guilherme Sakaji Kido
Keyword(s):  
Social Networks ◽  
Social Interactions ◽  
Online Social Networks ◽  
Topic Detection ◽  
Privacy And Security ◽  
Security Issues ◽  
Textual Content

Online Social Networks (OSNs), such as Twitter, offer attractive means of social interactions and communications, but also raise privacy and security issues. The OSNs provide valuable information to marketing and competitiveness based on users posts and opinions stored inside a huge volume of data from several themes, topics, and subjects. In order to mining the topics discussed on an OSN we present a novel application of Louvain method for TopicModeling based on communities detection in graphs by modularity. The proposed approach succeeded in finding topics in five different datasets composed of textual content from Twitter and Youtube. Another important contribution achieved was about the presence of texts posted by spammers. In this case, a particular behavior observed by graph community architecture (density and degree) allows the indication of a topic strength and the classification of it as natural or artificial. The later created by the spammers on OSNs.

Privacy in Online Social Networks

2021 ◽  
pp. 2078-2109
Author(s):  
Ramanpreet Kaur ◽  
Tomaž Klobučar ◽  
Dušan Gabrijelčič
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Online Social Networks ◽  
Privacy Protection ◽  
Privacy Preservation ◽  
Mitigation Strategies ◽  
Research Issues ◽  
Privacy Requirements ◽  
Privacy Threats

This chapter is concerned with the identification of the privacy threats to provide a feedback to the users so that they can make an informed decision based on their desired level of privacy. To achieve this goal, Solove's taxonomy of privacy violations is refined to incorporate the modern challenges to the privacy posed by the evolution of social networks. This work emphasizes on the fact that the privacy protection should be a joint effort of social network owners and users, and provides a classification of mitigation strategies according to the party responsible for taking these countermeasures. In addition, it highlights the key research issues to guide the research in the field of privacy preservation. This chapter can serve as a first step to comprehend the privacy requirements of online users and educate the users about their choices and actions in social media.

scholarly journals Filtering unwanted posts from online social networks (OSN)

2021 ◽  
Vol 10 (3) ◽  
pp. 1599-1602
Keyword(s):  
Social Networks ◽  
Social Networking ◽  
Online Social Networks ◽  
Personal Space ◽  
Online Social Networking ◽  
Important Thing ◽  
On Line ◽  
Index Terms ◽  
Textual Content ◽  
Filtering Procedure

Now a days, unexpectedly growing using on-line social networks (OSNs). Through this offerings user’s can speak and switch any data. The important thing downside of those Online Social Networking (OSN) offerings is the dearth of privateness for the user’s personal space. We use sample matching and textual content class set of rules for correct filtering results. We suggest a gadget permitting OSN customers to own a right awaymanages at the messages published on their walls. It might be a bendy region that rule primarily based totally gadget are used to lets in customers to customize the filtering procedure implemented to their user’s profiles. A system gaining knowledge of method robotically labeling messages in help of content-primarily based totally filtering. Index Terms: content-primarily based totally filtering, filtering rule, filtering gadget, system gaining knowledge of, on-line social networks

scholarly journals Análisis de la dinámica, la estructura y el contenido de los mensajes de Twitter: violencia sexual en #Cuéntalo

2022 ◽  
Author(s):  
Modesto Escobar ◽  
Elena Gil Moreno ◽  
Cristina Calvo López
Keyword(s):  
Social Networks ◽  
Content Analysis ◽  
Sexual Violence ◽  
Online Social Networks ◽  
Public Information ◽  
Redes Sociales ◽  
Social Scientists ◽  
New Type ◽  
Shared Narrative

Las redes sociales online se han ido convirtiendo en uno de los principales vehículos de comunicación y una de las mayores fuentes de información de actualidad. Esta creciente popularidad deja en evidencia la importancia de que los científicos sociales seamos capaces de analizar, interpretar y comprender en profundidad este nuevo tipo de herramientas. Este artículo tiene como objetivo mostrar los diversos métodos de análisis de la información pública obtenida a partir de una de estas redes, Twitter. Para ello tomamos como ejemplificación explicativa el caso #Cuéntalo, un episodio de narrativa compartida iniciado en esta red entre los días 26 y 28 de abril de 2018 tras la conocida sentencia de “La Manada”. A través de este caso se presentan aquí distintas metodologías para el estudio de los contenidos transmitidos, que van desde los análisis descriptivos más elementales hasta los análisis de contenido, pasando por la clasificación de actores relevantes y el descubrimiento de la estructura de las relaciones entre los protagonistas y sus mensajes. Los resultados muestran cómo esta polémica sentencia derivó en una conversación digital viral donde distintas usuarias (en especial periodistas, escritoras y activistas feministas) comenzaron a compartir sus relatos de situaciones de violencia sexual vividas por las participantes o sus conocidas usando esta etiqueta, siendo capaces de identificar a las principales protagonistas, las distintas relaciones que establecieron entre ellas y sus mensajes y los principales temas que se conformaron en torno a ellos. Online social networks have become one of the main communication vehicles and one of the greatest sources of current information. This growing popularity shows the importance of social scientists being able to analyze, interpret and understand in depth this new type of tools. This article aims to show the diverse methods of analysis of public information obtained from one of these networks, Twitter. To do this, we take as an explanatory example the case of #Cuéntalo, an episode of shared narrative that began on this network between April 26 and 28, 2018 after the well-known sentence of “La Manada”. Through this case, we present different methodologies for the study of broadcasted content, ranging from the most elementary descriptive tools to content analysis, passing through the classification of relevant actors and the discovery of the structure of the relationships amongst their protagonists and their messages. The results show how this controversial sentence led to a viral digital conversation where different users (especially journalists, writers, feminists and influencers) began to share their stories of situations of sexual violence experienced by the participants or their acquaintances using this label. Through this analysis, it was possible to identify the main protagonists, the different relationships that they established between them and their messages and the main themes that were formed around them.

scholarly journals A Framework for Detecting Intentions of Criminal Acts in Social Media: A Case Study on Twitter

Information ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 154 ◽  
Author(s):  
Ricardo Resende de Mendonça ◽  
Daniel Felix de Brito ◽  
Ferrucio de Franco Rosa ◽  
Júlio Cesar dos Reis ◽  
Rodrigo Bonacin
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Communication Planning ◽  
Flexible Model ◽  
Selection Of

Criminals use online social networks for various activities by including communication, planning, and execution of criminal acts. They often employ ciphered posts using slang expressions, which are restricted to specific groups. Although literature shows advances in analysis of posts in natural language messages, such as hate discourses, threats, and more notably in the sentiment analysis; research enabling intention analysis of posts using slang expressions is still underexplored. We propose a framework and construct software prototypes for the selection of social network posts with criminal slang expressions and automatic classification of these posts according to illocutionary classes. The developed framework explores computational ontologies and machine learning (ML) techniques. Our defined Ontology of Criminal Expressions represents crime concepts in a formal and flexible model, and associates them with criminal slang expressions. This ontology is used for selecting suspicious posts and decipher them. In our solution, the criminal intention in written posts is automatically classified relying on learned models from existing posts. This work carries out a case study to evaluate the framework with 8,835,290 tweets. The obtained results show its viability by demonstrating the benefits in deciphering posts and the effectiveness of detecting user’s intention in written criminal posts based on ML.

Privacy in Online Social Networks

2021 ◽  
pp. 567-598
Author(s):  
Ramanpreet Kaur ◽  
Tomaž Klobučar ◽  
Dušan Gabrijelčič
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Online Social Networks ◽  
Privacy Protection ◽  
Privacy Preservation ◽  
Mitigation Strategies ◽  
Research Issues ◽  
Privacy Requirements ◽  
Privacy Threats

This chapter is concerned with the identification of the privacy threats to provide a feedback to the users so that they can make an informed decision based on their desired level of privacy. To achieve this goal, Solove's taxonomy of privacy violations is refined to incorporate the modern challenges to the privacy posed by the evolution of social networks. This work emphasizes on the fact that the privacy protection should be a joint effort of social network owners and users, and provides a classification of mitigation strategies according to the party responsible for taking these countermeasures. In addition, it highlights the key research issues to guide the research in the field of privacy preservation. This chapter can serve as a first step to comprehend the privacy requirements of online users and educate the users about their choices and actions in social media.

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