Relevant bibliographies by topics / Online social networks

Academic literature on the topic 'Online social networks'

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Published: 4 June 2021
Last updated: 29 July 2024

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Journal articles on the topic "Online social networks"

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Melton, James, Robert Miller, and Michelle Salmona. "Online Social Networks." International Journal of Information Systems and Social Change 3, no. 2 (April 2012): 24–38. http://dx.doi.org/10.4018/ijissc.2012040102.

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Previous research has shown that many college students in the United States post content to social networking sites that they know would be considered inappropriate by employers and other authority figures. However, the phenomenon has not been extensively studied in cross-cultural context. To address this knowledge gap, a survey of college students in Australia, Denmark, the United Kingdom, and the United States was conducted. The study found a universal tendency among the four groups: students knew the content they were posting would be considered inappropriate by employers and other authority figures, but they chose to post it anyway. The article also reports on differences in the way this tendency was manifested and on related aspects of social networking across cultures, including decisions about privacy and information disclosure.
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Cardon, Peter W. "Online Social Networks." Business Communication Quarterly 72, no. 1 (July 22, 2008): 96–97. http://dx.doi.org/10.1177/1080569908330376.

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Faloutsos, Michalis, Thomas Karagiannis, and Sue Moon. "Online social networks." IEEE Network 24, no. 5 (September 2010): 4–5. http://dx.doi.org/10.1109/mnet.2010.5578911.

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Fu, Xiaoming, Andrea Passarella, Daniele Quercia, Alessandra Sala, and Thorsten Strufe. "Online Social Networks." Computer Communications 73 (January 2016): 163–66. http://dx.doi.org/10.1016/j.comcom.2015.11.005.

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Howard, Bill. "Analyzing online social networks." Communications of the ACM 51, no. 11 (November 2008): 14–16. http://dx.doi.org/10.1145/1400214.1400220.

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Gabielkov, Maksym, Ashwin Rao, and Arnaud Legout. "Sampling online social networks." ACM SIGCOMM Computer Communication Review 44, no. 4 (February 25, 2015): 127–28. http://dx.doi.org/10.1145/2740070.2631452.

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Mehta, Neil, and Ashish Atreja. "Online social support networks." International Review of Psychiatry 27, no. 2 (March 4, 2015): 118–23. http://dx.doi.org/10.3109/09540261.2015.1015504.

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Papagelis, Manos, Gautam Das, and Nick Koudas. "Sampling Online Social Networks." IEEE Transactions on Knowledge and Data Engineering 25, no. 3 (March 2013): 662–76. http://dx.doi.org/10.1109/tkde.2011.254.

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Garton, Laura, Caroline Haythornthwaite, and Barry Wellman. "Studying Online Social Networks." Journal of Computer-Mediated Communication 3, no. 1 (June 23, 2006): 0. http://dx.doi.org/10.1111/j.1083-6101.1997.tb00062.x.

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Angiani, Giulio, Paolo Fornacciari, Eleonora Iotti, Monica Mordonini, and Michele Tomaiuolo. "Participation in Online Social Networks." International Journal of Interactive Communication Systems and Technologies 8, no. 2 (July 2018): 36–55. http://dx.doi.org/10.4018/ijicst.2018070103.

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Why and how more and more people get involved and use social networking systems are critical topics in social network analysis (SNA). As a matter of fact, social networking systems bring online a growing number of acquaintances, for many different purposes. Both business interests and personal recreational goals are motivations for using online social networks (OSN) or other social networking systems. The participation in social networks is a phenomenon which has been studied with several theories, and SNA is useful for common business problems, e.g., launching distributed teams, retaining people with vital knowledge for the organization, improving access to knowledge and spreading ideas and innovation. Nevertheless, there are some difficulties, such as anti-social behaviors of participants, lack of incentives, organizational costs and risks. In this article, a survey of the basic features of SNA, participation theories and models are discussed, with emphasis on social capital, information spreading, motivations for participation, and anti-social behaviors of social network users.
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Dissertations / Theses on the topic "Online social networks"

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Vallapu, Sai Krishna. "Towards Network False Identity Detection in Online Social Networks." Thesis, Southern Illinois University at Edwardsville, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10246101.

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In this research, we focus on identifying false identities in social networks. We performed a detailed study on different string matching techniques to identify user profiles with real or fake identity. In this thesis, we focus on a specific case study on sex offenders. Sex offenders are not supposed to be online on social networking sites in few states. To identify the existence of offenders in social networks, we ran experiments to compare datasets downloaded from Facebook and offender registries. To identify the most suitable string matching technique to solve this particular problem, we performed experiments on various methods and utilized the most appropriate technique, the Jaro-Winkler algorithm. The major contribution of our research is a weight based scoring function that is capable of identifying user records with full or partial data revealed in social networks. Based on our data samples created using metadata information of Facebook, we were able to identify the sex offender profiles with real identity and seventy percent of the sex offenders with partial information.

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Rahman, Mahmudur. "Data Verifications for Online Social Networks." FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/etd/2299.

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Social networks are popular platforms that simplify user interaction and encourage collaboration. They collect large amounts of media from their users, often reported from mobile devices. The value and impact of social media makes it however an attractive attack target. In this thesis, we focus on the following social media vulnerabilities. First, review centered social networks such as Yelp and Google Play have been shown to be the targets of significant search rank and malware proliferation attacks. Detecting fraudulent behaviors is thus paramount to prevent not only public opinion bias, but also to curb the distribution of malware. Second, the increasing use of mobile visual data in news networks, authentication and banking applications, raises questions of its integrity and credibility. Third, through proof-of- concept implementations, we show that data reported from wearable personal trackers is vulnerable to a wide range of security and privacy attacks, while off-the-shelves security solutions do not port gracefully to the constraints introduced by trackers. In this thesis we propose novel solutions to address these problems. First, we introduce Marco, a system that leverages the wealth of spatial, temporal and network information gleaned from Yelp, to detect venues whose ratings are impacted by fraudulent reviews. Second, we propose FairPlay, a system that correlates review activities, linguistic and behavioral signals gleaned from longitudinal app data, to identify not only search rank fraud but also malware in Google Play, the most popular Android app market. Third, we describe Movee, a motion sensor based video liveness verification system, that analyzes the consistency between the motion inferred from the simultaneously and independently captured camera and inertial sensor streams. Finally, we devise SensCrypt, an efficient and secure data storage and communication protocol for affordable and lightweight personal trackers. We provide the correctness and efficacy of our solutions through a detailed theoretic and experimental analysis.
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Webberley, William. "Inferring interestingness in online social networks." Thesis, Cardiff University, 2014. http://orca.cf.ac.uk/68758/.

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Information sharing and user-generated content on the Internet has given rise to the increased presence of uninteresting and ‘noisy’ information in media streams on many online social networks. Although there is a lot of ‘interesting’ information also shared amongst users, the noise increases the cognitive burden in terms of the users’ abilities to identify what is interesting and may increase the chance of missing content that is useful or important. Additionally, users on such platforms are generally limited to receiving information only from those that they are directly linked to on the social graph, meaning that users exist within distinct content ‘bubbles’, further limiting the chance of receiving interesting and relevant information from outside of the immediate social circle. In this thesis, Twitter is used as a platform for researching methods for deriving “interestingness” through popularity as given by the mechanism of retweeting, which allows information to be propagated further between users on Twitter’s social graph. Retweet behaviours are studied, and features; such as those surrounding Tweet audience, information redundancy, and propagation depth through path-length, are uncovered to help relate retweet action to the underlying social graph and the communities it represents. This culminates in research into a methodology for assigning scores to Tweets based on their ‘quality’, which is validated and shown to perform well in various situations.
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Baatarjav, Enkh-Amgalan. "Privacy Management for Online Social Networks." Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc283816/.

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One in seven people in the world use online social networking for a variety of purposes -- to keep in touch with friends and family, to share special occasions, to broadcast announcements, and more. The majority of society has been bought into this new era of communication technology, which allows everyone on the internet to share information with friends. Since social networking has rapidly become a main form of communication, holes in privacy have become apparent. It has come to the point that the whole concept of sharing information requires restructuring. No longer are online social networks simply technology available for a niche market; they are in use by all of society. Thus it is important to not forget that a sense of privacy is inherent as an evolutionary by-product of social intelligence. In any context of society, privacy needs to be a part of the system in order to help users protect themselves from others. This dissertation attempts to address the lack of privacy management in online social networks by designing models which understand the social science behind how we form social groups and share information with each other. Social relationship strength was modeled using activity patterns, vocabulary usage, and behavioral patterns. In addition, automatic configuration for default privacy settings was proposed to help prevent new users from leaking personal information. This dissertation aims to mobilize a new era of social networking that understands social aspects of human network, and uses that knowledge to honor users' privacy.
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Cox, Shirley A. "Online social network member attitude toward online advertising formats /." Online version of thesis, 2010. http://hdl.handle.net/1850/11588.

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Alim, Sophia. "Vulnerability in online social network profiles : a framework for measuring consequences of information disclosure in online social networks." Thesis, University of Bradford, 2011. http://hdl.handle.net/10454/5507.

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The increase in online social network (OSN) usage has led to personal details known as attributes being readily displayed in OSN profiles. This can lead to the profile owners being vulnerable to privacy and social engineering attacks which include identity theft, stalking and re identification by linking. Due to a need to address privacy in OSNs, this thesis presents a framework to quantify the vulnerability of a user's OSN profile. Vulnerability is defined as the likelihood that the personal details displayed on an OSN profile will spread due to the actions of the profile owner and their friends in regards to information disclosure. The vulnerability measure consists of three components. The individual vulnerability is calculated by allocating weights to profile attribute values disclosed and neighbourhood features which may contribute towards the personal vulnerability of the profile user. The relative vulnerability is the collective vulnerability of the profiles' friends. The absolute vulnerability is the overall profile vulnerability which considers the individual and relative vulnerabilities. The first part of the framework details a data retrieval approach to extract MySpace profile data to test the vulnerability algorithm using real cases. The profile structure presented significant extraction problems because of the dynamic nature of the OSN. Issues of the usability of a standard dataset including ethical concerns are discussed. Application of the vulnerability measure on extracted data emphasised how so called 'private profiles' are not immune to vulnerability issues. This is because some profile details can still be displayed on private profiles. The second part of the framework presents the normalisation of the measure, in the context of a formal approach which includes the development of axioms and validation of the measure but with a larger dataset of profiles. The axioms highlight that changes in the presented list of profile attributes, and the attributes' weights in making the profile vulnerable, affect the individual vulnerability of a profile. iii Validation of the measure showed that vulnerability involving OSN profiles does occur and this provides a good basis for other researchers to build on the measure further. The novelty of this vulnerability measure is that it takes into account not just the attributes presented on each individual profile but features of the profiles' neighbourhood.
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Sáez-Trumper, Diego. "Finding relevant people in online social networks." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/283658.

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The objective of this thesis is to develop novel techniques to find relevant people in Online Social Networks (OSN). To that end, we consider different notions of relevance, taking the point of view of the OSN providers (like Facebook) and advertisers, as well as considering the people who are trying to push new ideas and topics on the network. We go beyond people's popularity, showing that the users with a lot of followers are not necessarily the most relevant. Specifically, we develop three algorithms that allow to: (i) compute the monetary value that each user produces for OSN provider; (ii) find users that push new ideas and create trends; and (iii) a recommender system that allows advertisers (focusing in local shops, like restaurants or pubs) to find potential customers. Furthermore, we also provide useful insights about users' behavior according to their relevance and popularity, showing - among other things - that most active users are usually more relevant than the popular ones. Moreover, we show that usually very popular users arrive late to the new trends, and that there are less popular, but very active users that generate value and push new ideas in the network.
L'objectiu d'aquesta tesi és desenvolupar noves tècniques per trobar persones rellevants en les Xarxes Socials a Internet. Així doncs, considerem diferents nocions de rellevància, tenint en compte el punt de vista dels prove ïdors del servei (com Facebook) i dels anunciants, però també de persones que intenten proposar noves idees i temes a la xarxa. La nostra investigació va més enllà de la popularitat de les persones, mostra que els usuaris amb molts seguidors no són necessàriament els més rellevants. Específicament, desenvolupem tres algorismes que permeten: (i) calcular el valor (monetari) que cada usuari produeix per al prove ïdor del servei; (ii) trobar usuaris que proposen noves idees i creen tendències; i (iii) un sistema de recomanació que permet als anunciants (centrant-nos en botigues locals, com ara un restaurant o un pub) trobar clients potencials. Addicionalment, lliurem informació útil sobre el comportament dels usuaris segons la seva rellevància i popularitat, mostrant, entre altres coses, que els usuaris més actius solen ser més rellevants que els populars. A més a més, mostrem que normalment els usuaris molt populars arriben tard a les noves tendències, mentre que usuaris de menor popularitat, però molt actius, generen valor i fomenten noves idees a la xarxa .
El objetivo de esta tesis es desarrollar nuevas técnicas para encontrar personas relevantes en las Redes Sociales en Internet. Para ello, consideramos diferentes nociones de relevancia, tomando el punto de vista de los proveedores del servicio (como Facebook) y de los anunciantes, pero también de las personas que intentan proponer nuevas ideas y temas en la red. Nuestra investigación va más allá de la popularidad de las personas, mostrando que los usuarios con muchos seguidores no son necesariamente los más relevantes. Espeficamente, desarollamos tres algoritmos que permiten: (i) calcular el valor (monetario) que cada usuario produce para el proveedor del servicio; (ii) encontrar usuarios que proponen nuevas ideas y crean tendencias; y (iii) un sistema de recomendación que permite a los anunciantes (centrándonos en tiendas locales, tales como un restaurant o un pub) encontrar potenciales clientes. Adicionalmente, proporcionamos información útil sobre el comportamiento de los usuarios según su relevancia y popularidad, mostrando - entre otras cosas - que los usuarios más activos suelen ser más relevantes que los populares. Más aún, mostramos que normalmente los usuarios muy populares llegan tarde a las nuevas tendencias, y que existen usuarios menos populares, pero muy activos que generan valor y fomentan nuevas ideas en la red.
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Recalde, Lorena. "Modeling users preferences in online social networks." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/663756.

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L'objectiu d'aquesta tesi és desenvolupar nous i diversos mètodes per modelar les preferències dels usuaris a les Xarxes Socials Online. Els mètodes proposats tenen com a finalitat ser aplicats en àrees de recerca com la Personalització o Recomanació d'ítems i la Detecció de Grups d'Usuaris amb gustos similars. Aquests mètodes poden ser agrupats en dos tipus: i) mètodes basats en tècniques d'anàlisi de textos (Part I, Capítols del 3 al 5) i ii) mètodes basats en teoria de grafs (Part II, Capítols 6 i 7). Amb els mètodes plantejats a la Part I és possible determinar el nivell d'interès dels usuaris en temes que són compartits en plataformes de microblogging. Hem pres com a cas d'estudi la participació digital de tweeters a la política. Els mètodes proposats a la Part II busquen definir un paper pels usuaris de les Xarxes Socials, ja sigui com a creadors o generadors de contingut i distribuïdors o consumidors de contingut. Hem plantejat un mètode on usuaris amb interessos similars però amb diferent rols són agrupats en una mateixa comunitat, de manera que els nous continguts es propaguen més ràpidament.
El objetivo de esta tesis es desarrollar nuevos y diversos métodos para modelar las preferencias de los usuarios en las Redes Sociales Online. Los métodos propuestos tienen como finalidad ser aplicados en áreas de investigación como la Personalización o Recomendación de ítems y la Detección de Grupos de Usuarios con gustos similares. Dichos métodos pueden ser agrupados en dos tipos: i) métodos basados en técnicas de análisis de texto (Parte I, Capítulos del 3 al 5) y ii) métodos basados en teoría de grafos (Parte II, Capítulos 6 y 7). Con los métodos planteados en la Parte I es posible determinar el nivel de interés de los usuarios en temas que son compartidos en plataformas de microblogging. Hemos tomado como caso de estudio la participación digital de tweeters en la política. Los métodos propuestos en la Parte II buscan definir un rol para los usuarios en Redes Sociales, ya sea como creadores o generadores de contenido y distribuidores o consumidores de contenido. Hemos planteado un método donde usuarios con intereses similares pero con distinto rol, son agrupados en una misma comunidad de forma que nuevo contenido se propague más rápidamente.
The objective of this thesis is to develop new and diverse methods to model the preferences of the users in the Online Social Networks. The proposed methods are intended to be applied in areas of research such as Personalization or Recommendation of items and the detection of groups of users with similar tastes. These methods can be grouped into two types: i) methods based on text analysis techniques (Chapters 3 to 5) and ii) methods based on graph theory (Chapters 6 and 7). With the methods proposed in i) it is possible to determine the level of interest of users on topics that are shared on microblogging platforms. We have taken as a case study the digital participation of tweeters in politics. The methods proposed in ii) seek to define a role for users in social networks, whether as creators or content generators and distributors or content consumers. We have proposed a method where users with similar interests but with different roles, are grouped in the same community so that new content spreads more quickly.
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Bhardwaj, Shally. "Personality Assessment Using Multiple Online Social Networks." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31734.

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Personality plays an important role in various aspects of our daily life. It is being used in many application scenarios such as i) personalized marketing and advertisement of commercial products, ii) designing personalized ambient environments, iii) personalized avatars in virtual world, and iv) by psychologists to treat various mental and personality disorders. Traditional methods of personality assessment require a long questionnaire to be completed, which is time consuming. On the other hand, several works have been published that seek to acquire various personality traits by analyzing Internet usage statistics. Researchers have used Facebook, Twitter, YouTube, and various other websites to collect usage statistics. However, we are still far from a successful outcome. This thesis uses a range of divergent features of Facebook and LinkedIn social networks, both separately and collectively, in order to achieve better results. In this work, the big five personality trait model is used to analyze the five traits: openness to experience, conscientiousness, extroversion, agreeableness, and neuroticism. The experimental results show that the accuracy of personality detection improves with the use of complementary features of multiple social networks (Facebook and LinkedIn, in our case) for openness, conscientiousness, agreeableness, and neuroticism. However, for extroversion we found that the use of only LinkedIn features provides better results than the use of only Facebook features or both Facebook and LinkedIn features.
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Ahmad, Waqar, and Asim Riaz. "Predicting Friendship Levels in Online Social Networks." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3351.

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Abstract Context: Online social networks such as Facebook, Twitter, and MySpace have become the preferred interaction, entertainment and socializing facility on the Internet. However, these social network services also bring privacy issues in more limelight than ever. Several privacy leakage problems are highlighted in the literature with a variety of suggested countermeasures. Most of these measures further add complexity and management overhead for the user. One ignored aspect with the architecture of online social networks is that they do not offer any mechanism to calculate the strength of relationship between individuals. This information is quite useful to identify possible privacy threats. Objectives: In this study, we identify users’ privacy concerns and their satisfaction regarding privacy control measures provided by online social networks. Furthermore, this study explores data mining techniques to predict the levels/intensity of friendship in online social networks. This study also proposes a technique to utilize predicted friendship levels for privacy preservation in a semi-automatic privacy framework. Methods: An online survey is conducted to analyze Facebook users’ concerns as well as their interaction behavior with their good friends. On the basis of survey results, an experiment is performed to justify practical demonstration of data mining phases. Results: We found that users are concerned to save their private data. As a precautionary measure, they restrain to show their private information on Facebook due to privacy leakage fears. Additionally, individuals also perform some actions which they also feel as privacy vulnerability. This study further identifies that the importance of interaction type varies while communication. This research also discovered, “mutual friends” and “profile visits”, the two non-interaction based estimation metrics. Finally, this study also found an excellent performance of J48 and Naïve Bayes algorithms to classify friendship levels. Conclusions: The users are not satisfied with the privacy measures provided by the online social networks. We establish that the online social networks should offer a privacy mechanism which does not require a lot of privacy control effort from the users. This study also concludes that factors such as current status, interaction type need to be considered with the interaction count method in order to improve its performance. Furthermore, data mining classification algorithms are tailor-made for the prediction of friendship levels.
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Books on the topic "Online social networks"

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Hillstrom, Laurie Collier. Online social networks. Detroit: Lucent Books, 2010.

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Van Gunten, Tod, and Karen Gregory. Analyzing Online Social Networks. 1 Oliver’s Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2022. http://dx.doi.org/10.4135/9781529609585.

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Tagarelli, Andrea, and Roberto Interdonato. Mining Lurkers in Online Social Networks. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00229-9.

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Carminati, Barbara, Elena Ferrari, and Marco Viviani. Security and Trust in Online Social Networks. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-031-02339-2.

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Özyer, Tansel, and Reda Alhajj, eds. Machine Learning Techniques for Online Social Networks. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89932-9.

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author, Ferrari Elena 1968, and Viviani Marco author, eds. Security and trust in online social networks. San Rafael, California]: Morgan & Claypool Publishers, 2014.

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Spivet, Bonnie. Using social networks. New York, NY: PowerKids Press, 2012.

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Bambina, Antonina. Online social support: The interplay of social networks and computer-mediated communication. Youngstown, NY: Cambria Press, 2007.

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Abbassi, Zeinab. Characterizing and Leveraging Social Phenomena in Online Networks. [New York, N.Y.?]: [publisher not identified], 2016.

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Online Social Networks. Elsevier, 2015. http://dx.doi.org/10.1016/c2014-0-02436-7.

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Book chapters on the topic "Online social networks"

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Symeonidis, Panagiotis, Dimitrios Ntempos, and Yannis Manolopoulos. "Online Social Networks." In SpringerBriefs in Electrical and Computer Engineering, 21–34. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0286-6_3.

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Datta, Anwitaman, Sonja Buchegger, Le-Hung Vu, Thorsten Strufe, and Krzysztof Rzadca. "Decentralized Online Social Networks." In Handbook of Social Network Technologies and Applications, 349–78. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-7142-5_17.

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Beye, Michael, Arjan J. P. Jeckmans, Zekeriya Erkin, Pieter Hartel, Reginald L. Lagendijk, and Qiang Tang. "Privacy in Online Social Networks." In Computational Social Networks, 87–113. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4051-1_4.

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Abdesslem, Fehmi Ben, Iain Parris, and Tristan Henderson. "Reliable Online Social Network Data Collection." In Computational Social Networks, 183–210. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4054-2_8.

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Kazienko, Przemysław, and Katarzyna Musiał. "Social Capital in Online Social Networks." In Lecture Notes in Computer Science, 417–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11893004_54.

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Eliassi-Rad, Tina. "Social Order in Online Social Networks." In Encyclopedia of Social Network Analysis and Mining, 1–3. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7163-9_287-1.

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Eliassi-Rad, Tina. "Social Order in Online Social Networks." In Encyclopedia of Social Network Analysis and Mining, 1918–20. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6170-8_287.

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Eliassi-Rad, Tina. "Social Order in Online Social Networks." In Encyclopedia of Social Network Analysis and Mining, 2760–61. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7131-2_287.

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Chmiel, Anna, Julian Sienkiewicz, Georgios Paltoglou, Kevan Buckley, Marcin Skowron, Mike Thelwall, Arvid Kappas, and Janusz A. Hołyst. "Collective Emotions Online." In Lecture Notes in Social Networks, 59–74. Vienna: Springer Vienna, 2014. http://dx.doi.org/10.1007/978-3-7091-1340-0_4.

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Mamun, Mohammad, Muhammad Al-Digeil, and Sherif Saad Ahmed. "Profiling Online Users." In Securing Social Networks in Cyberspace, 221–40. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003134527-14.

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Conference papers on the topic "Online social networks"

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Baeza-Yates, Ricardo, and Diego Saez-Trumper. "Online social networks." In the 22nd International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2487788.2487977.

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Kumar, Ravi. "Online social networks." In the Second ACM International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1498759.1498762.

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Erlandsson, Fredrik, Roozbeh Nia, Martin Boldt, Henric Johnson, and S. Felix Wu. "Crawling Online Social Networks." In 2015 Second European Network Intelligence Conference (ENIC). IEEE, 2015. http://dx.doi.org/10.1109/enic.2015.10.

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Terevinto, Pablo Nicolas, Miguel Perez, Josep Domenech, Jose A. Gil, and Ana Pont. "Benchmarking online social networks." In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2016. http://dx.doi.org/10.1109/asonam.2016.7752229.

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Koot, Gijs, Mirjam A. A. Huis in Veld, Joost Hendricksen, Rianne Kaptein, Arnout De Vries, and Egon L. Van Den Broek. "Foraging Online Social Networks." In 2014 IEEE Joint Intelligence and Security Informatics Conference (JISIC). IEEE, 2014. http://dx.doi.org/10.1109/jisic.2014.62.

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Chiu, Terry Hui-Ye, and ShyMin Chen. "Propagating online social networks." In ASONAM '13: Advances in Social Networks Analysis and Mining 2013. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2492517.2500277.

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Gabielkov, Maksym, Ashwin Rao, and Arnaud Legout. "Sampling online social networks." In SIGCOMM'14: ACM SIGCOMM 2014 Conference. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2619239.2631452.

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Ghosh, Saptarshi, Gautam Korlam, and Niloy Ganguly. "Spammers' networks within online social networks." In the 20th international conference companion. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1963192.1963214.

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Neglia, Giovanni, Xiuhui Ye, Maksym Gabielkov, and Arnaud Legout. "How to network in online social networks." In IEEE INFOCOM 2014 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2014. http://dx.doi.org/10.1109/infcomw.2014.6849336.

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Sivaraman, Nirmal Kumar, Sakthi Balan Muthiah, Pushkal Agarwal, and Lokesh Todwal. "On Social Synchrony in Online Social Networks." In WebSci '17: ACM Web Science Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3091478.3098881.

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Reports on the topic "Online social networks"

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Campos Freire, F., D. Rivera Rogel, and C. Rodríguez. Presence and impact of Andean universities in online social networks. Revista Latina de Comunicación Social, September 2014. http://dx.doi.org/10.4185/rlcs-2014-1025en.

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Valerio-Ureña, G., and DJ Herrera-Murillo. Online social networks as a communication channel for open access journals. Revista Latina de Comunicación Social, November 2017. http://dx.doi.org/10.4185/rlcs-2017-1222en.

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Gil-Clavel, Beatriz Sofía, Emilio Zagheni, and Valeria Bordone. Close social networks among older adults: the online and offline perspectives. Rostock: Max Planck Institute for Demographic Research, October 2020. http://dx.doi.org/10.4054/mpidr-wp-2020-035.

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Freedman, Seth, and Ginger Zhe Jin. The Information Value of Online Social Networks: Lessons from Peer-to-Peer Lending. Cambridge, MA: National Bureau of Economic Research, January 2014. http://dx.doi.org/10.3386/w19820.

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Hotsur, Oksana. SOCIAL NETWORKS AND BLOGS AS TOOLS PR-CAMPAIGN IMPLEMENTATIONS. Ivan Franko National University of Lviv, March 2021. http://dx.doi.org/10.30970/vjo.2021.50.11110.

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The article deals with the ways in which social networks and the blogosphere influence the formation and implementation of a PR campaign. Examples from the political sphere (election campaigns, initiatives), business (TV brands, traditional and online media) have revealed the opportunities that Facebook, Telegram, Twitter, YouTube and blogs promote in promoting advertising, ideas, campaigns, thoughts, or products. Author blogs created on special websites or online media may not be as much of a tool in PR as an additional tool on social media. It is noted that choosing a blog as the main tool of PR campaign has both positive and negative points. Social networks intervene in the sphere of human life, become a means of communication, promotion, branding. The effectiveness of social networks has been evidenced by such historically significant events as Brexit, the Arab Spring, and the Revolution of Dignity. Special attention was paid to the 2019 presidential election. Based on the analysis of individual PR campaigns, the reasons for successful and unsuccessful campaigns from the point of view of network communication, which provide unlimited multimedia and interactive tools for PR, are highlighted. In fact, these concepts significantly affect the effectiveness of the implementation of PR-campaign, its final effectiveness, which is determined by the achievement of goals. Attention is drawn to the culture of communication during the PR campaign, as well as the concepts of “trolls”, “trolling”, “bots”, “botoin industry”. The social communication component of these concepts is unconditional. Choosing a blog as the main tool of a marketing campaign has both positive and negative aspects. Only a person with great creative potential can run and create a blog. In addition, it takes a long time. In fact, these two points are losing compared to other internet marketing tools. Further research is interesting in two respects. First, a comparison of the dynamics of the effectiveness of PR-campaign tools in Ukraine in 2020 and in the past, in particular, at the dawn of state independence. Secondly, to investigate how/or the concept of PR-campaigns in social networks and blogs is constantly changing.
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Mayande, Nitin. Network Structure, Network Flows and the Phenomenon of Influence in Online Social Networks: An Exploratory Empirical Study of Twitter Conversations about YouTube Product Categories. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2463.

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Droogan, Julian, Lise Waldek, Brian Ballsun-Stanton, and Jade Hutchinson. Mapping a Social Media Ecosystem: Outlinking on Gab & Twitter Amongst the Australian Far-right Milieu. RESOLVE Network, September 2022. http://dx.doi.org/10.37805/remve2022.6.

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Attention to the internet and the online spaces in which violent extremists interact and spread content has increased over the past decades. More recently, that attention has shifted from understanding how groups like the self-proclaimed Islamic State use the internet to spread propaganda to understanding the broader internet environment and, specifically, far-right violent extremist activities within it. This focus on how far right violent extremist—including far-right racially and ethnically motivated violent extremists (REMVEs) within them—create, use, and exploit the online networks in which they exist to promote their hateful ideology and reach has largely focused on North America and Europe. However, in recent years, examinations of those online dynamics elsewhere, including in Australia, is increasing. Far right movements have been active in Australia for decades. While these movements are not necessarily extremist nor violent, understanding how violent far right extremists and REMVEs interact within or seek to exploit these broader communities is important in further understanding the tactics, reach, and impact of REMVEs in Australia. This is particularly important in the online space access to broader networks of individuals and ideas is increasingly expanding. Adding to a steadily expanding body of knowledge examining online activities and networks of both broader far right as well as violent extremist far right populations in Australia, this paper presents a data-driven examination of the online ecosystems in which identified Australian far-right violent extremists exist and interact,1 as mapped by user generated uniform resource locators (URL), or ‘links’, to internet locations gathered from two online social platforms—Twitter and Gab. This link-based analysis has been used in previous studies of online extremism to map the platforms and content shared in online spaces and provide further detail on the online ecosystems in which extremists interact. Data incorporating the links was automatically collected from Twitter and Gab posts from users existing within the online milieu in which those identified far right extremists were connected. The data was collected over three discrete one-month periods spanning 2019, the year in which an Australian far right violent extremist carried out the Christchurch attack. Networks of links expanding out from the Twitter and Gab accounts were mapped in two ways to explore the extent and nature of the online ecosystems in which these identified far right Australian violent extremists are connected, including: To map the extent and nature of these ecosystems (e.g., the extent to which other online platforms are used and connected to one another), the project mapped where the most highly engaged links connect out to (i.e., website domain names), and To explore the nature of content being spread within those ecosystems, what sorts of content is found at the end of the most highly engaged links. The most highly engaged hashtags from across this time are also presented for additional thematic analysis. The mapping of links illustrated the interconnectedness of a social media ecosystem consisting of multiple platforms that were identified as having different purposes and functions. Importantly, no links to explicitly violent or illegal activity were identified among the top-most highly engaged sites. The paper discusses the implications of the findings in light of this for future policy, practice, and research focused on understanding the online ecosystems in which identified REMVE actors are connected and the types of thematic content shared and additional implications in light of the types of non-violent content shared within them.
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Sánchez-Pájaro, Andrés, Tonatiuh Barrientos-Gutiérrez, and Carolina Pérez-Ferrer. Social and built environment interventions to prevent alcohol, tobacco, and legal cannabis use: a scoping review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, May 2023. http://dx.doi.org/10.37766/inplasy2023.5.0101.

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Eligibility criteria: We will use the following inclusion criteria: 1) Document must mention by name or describe at least one intervention, strategy, program or policy to prevent alcohol, tobacco and legal cannabis use. 2) Document must contain enough information for the researchers to determine if the intervention, strategy, program or policy was aimed at modifying the social and/or built environment. 3) Intervention, strategy, program or policy must have been aimed at modifying the social and/or built environment, using the following definitions: Social environment: “…the immediate physical surroundings, social relationships, and cultural milieus within which defined groups of people function and interact…Social environments can be experienced at multiple scales, often simultaneously, including households, kin networks, neighborhoods, towns and cities, and regions…”; Built environment: “the surroundings or conditions designed and built through human intervention, where a person lives or operates”. 4) Document must mention that intervention/strategy/program/policy has been implemented within the last 30 years (1992-2022), whatever the setting, time frame, or subpopulation. 5) Document must be within the body of scientific literature (peer-reviewed articles, research journal commentaries, editorials, or perspective pieces), be a published book or book chapter, a government, multinational organization or non-profit organization report, or a dissertation/thesis. 6) Document must not be a conference abstract, public letter, speech transcript, budget report, independent website post or blog, or news article. 7) Document must be in English or Spanish. 8) Document must be open-source, publicly available online, or accessible through the INSP’s library services.
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Bowman, Elizabeth K., Nkonko Kamwangamalu, Heather Roy, Alla Tovares, Sue Kase, Michelle Vanni, Mugizi R. Rwebangira, and Mohamed Chouikha. Exploring Social Meaning in Online Bilingual Text through Social Network Analysis. Fort Belvoir, VA: Defense Technical Information Center, September 2015. http://dx.doi.org/10.21236/ada622463.

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Pererva, Victoria V., Olena O. Lavrentieva, Olena I. Lakomova, Olena S. Zavalniuk, and Stanislav T. Tolmachev. The technique of the use of Virtual Learning Environment in the process of organizing the future teachers' terminological work by specialty. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3868.

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This paper studies the concept related to E-learning and the Virtual Learning Environment (VLE) and their role in organizing future teachers’ terminological work by specialty. It is shown the creation and use of the VLE is a promising approach in qualitative restructuring of future specialists’ vocation training, a suitable complement rather than a complete replacement of traditional learning. The concept of VLE has been disclosed; its structure has been presented as a set of components, such as: the Data-based component, the Communication-based, the Management-and-Guiding ones, and the virtual environments. Some VLE’s potential contributions to the organization of terminological work of future biology teachers’ throughout a traditional classroom teaching, an independent work, and during the field practices has been considered. The content of professionally oriented e-courses “Botany with Basis of Geobotany” and “Latin. Botany Terminology” has been revealed; the ways of working with online definer (guide), with UkrBIN National Biodiversity Information Network, with mobile apps for determining the plant species, with digital virtual herbarium, with free software have been shown. The content of students’ activity in virtual biological laboratories and during virtual tours into natural environment has been demonstrated. The explanations about the potential of biological societies in social networks in view of students’ terminology work have been given. According to the results of empirical research, the expediency of using VLEs in the study of professional terminology by future biology teachers has been confirmed.
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