Browsing by Subject "social networks"
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Item Analyzing Social Networks on the Semantic Web(IEEE, 2005-01-01) Ding, Li; Finin, Tim; Joshi, AnupamWe report on a recent study of the way FOAF and other semantic web ontologies are being used to describe people and their social relations.Item Online Translanguaging Practices Among Hispanic International Students in the United States(2022-01-01) Reguera Gomez, Cristina; Yoon, Kyung-Eun; Language, Literacy & Culture; Intercultural CommunicationThe purpose of this research is to examine the translanguaging practices on social networks of Hispanic international students in American universities, with a focus on how they translanguage and what social functions their translanguaging practices have. To answer these questions, this study examines the posts and messages of five participants through critical and multilingual discourse analysis. The results show that participants translanguage within the lexical, at the lexical, and at the sentential level, while evidencing a high level of creativity. The type of translanguage and its frequency is closely linked to the audience and the social network used: participants translanguage more frequently and in more diverse ways when communicating with fellow SpanishEnglish bilingual international students, while expressing different identities and different emotions. The present study suggests that translanguaging is more complex product than a mixture of two languages and its presence is highly reliant on the audience.Item Semantic Analytics on Social Networks: Experiences in Addressing the Problem of Conflict of Interest Detection(ACM, 2006-05-23) Aleman-Meza, Boanerges; Nagarajan, Meenakshi; Ramakrishnan, Cartic; Ding, Li; Kolari, Pranam; Sheth, Amit; Arpinar, Budak; Joshi, Anupam; Finin, TimIn this paper, we describe a Semantic Web application that detects Conflict of Interest relationships among potential reviewers and authors of scientific papers. This application discovers various "semantic associations" between the reviewers and authors in a populated ontology to determine a degree of Conflict of Interest. This ontology is built by integrating entities and relationships from two social networks, namely 'knows' from a FOAF (Friendof- a-Friend) social network, and 'co-author' from the underlying co-authorship network of the DBLP bibliography. We describe our experiences on development of this application in the context of a class of Semantic Web applications which have important research and engineering challenges in common. In addition, we present an evaluation of our approach for real-life COI detection.Item Uninformed Adversarial Community Detection(2018-01-01) Hein, Ethan; Oates, James T; Computer Science and Electrical Engineering; Computer ScienceAn increasingly popular branch of graph theory is the concept of community detection. However, the field of adversarial community detection currently has very little scientific literature. Initial tests suggest that an attacker in an adversarial community detection situation may not need specific information about a network as a whole in order to effectively mask a single community. In some cases, the attacker can achieve this with even random attacks on the network. However, some community detection algorithms are far more robust than others, and so the results of these tests vary greatly as a result.