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Discovering similar Twitter accounts using semantics [article]

Gerasimos Razis, Ioannis Anagnostopoulos
2015 arXiv   pre-print
Towards this direction, we introduce a methodology for discovering and suggesting similar Twitter accounts, based entirely on their disseminated content in terms of Twitter entities used.  ...  Many of these entities are used in common by many accounts.  ...  Case study evaluation In the previous section, an implementation of the proposed framework for discovering similar Twitter accounts was presented along with some results regarding that use case.  ... 
arXiv:1506.00100v1 fatcat:uk6kz7c42bhl5f6s7caakrhjhy

Modeling Influence with Semantics in Social Networks: a Survey [article]

Gerasimos Razis, Ioannis Anagnostopoulos, Sherali Zeadally
2018 arXiv   pre-print
In this work, we present a systematic review across i) online social influence metrics, properties, and applications and ii) the role of semantic in modeling OSNs information.  ...  We end up with the conclusion that both areas can jointly provide useful insights towards the qualitative assessment of viral user-generated content, as well as for modeling the dynamic properties of influential  ...  A framework for discovering similar accounts in Twitter based only on the "List" feature is proposed in [64] .  ... 
arXiv:1801.09961v3 fatcat:mnwvsphxgjdcvlu6vsn6g6pv5e

SMS: A Framework for Service Discovery by Incorporating Social Media Information

Tingting Liang, Liang Chen, Jian Wu, Guandong Xu, Zhaohui Wu
2016 IEEE Transactions on Services Computing  
Specifically, we present different methods to measure four social factors (semantic similarity, popularity, activity, decay factor) collected from Twitter.  ...  Latent Semantic Indexing (LSI) model is applied to mine semantic information of services from meta-data of Twitter Lists that contains them.  ...  services' Twitter account.  ... 
doi:10.1109/tsc.2016.2631521 fatcat:an2fqd4wtbaw5gy4m5xae7di2i

Semantic Enrichment of Twitter Posts for User Profile Construction on the Social Web [chapter]

Fabian Abel, Qi Gao, Geert-Jan Houben, Ke Tao
2011 Lecture Notes in Computer Science  
However, automatically inferring the semantic meaning of Twitter posts is a non-trivial problem. In this paper we investigate semantic user modeling based on Twitter posts.  ...  Representing the semantics of individual Twitter activities and modeling the interests of Twitter users would allow for personalization and therewith countervail the information overload.  ...  The connections between the semantically enriched news articles and Twitter posts enable us to construct a rich RDF graph that represents the microblogging activities in a semantically well-defined context  ... 
doi:10.1007/978-3-642-21064-8_26 fatcat:sqgr3l2od5ab7idofzqfytd3ze

Analyzing Discourse Communities with Distributional Semantic Models

Igor Brigadir, Derek Greene, Pádraig Cunningham
2015 Proceedings of the ACM Web Science Conference on ZZZ - WebSci '15  
Distributional Semantic Models (DSMs).  ...  This approach considers changes in word semantics, both over time and between communities with differing viewpoints.  ...  Our approach can be used to discover similar patterns, where predicting a set of contexts given a word can be interpreted as an aggregation of concordance lines, drawing an analogy between the training  ... 
doi:10.1145/2786451.2786470 dblp:conf/websci/BrigadirGC15 fatcat:k5bpyez67bbp3avny63hpiksae

YouTube Video Promotion by Cross-Network Association: @Britney to Advertise Gangnam Style

Ming Yan, Jitao Sang, Changsheng Xu, M. Shamim Hossain
2015 IEEE transactions on multimedia  
Since YouTube videos and Twitter followees  ...  introduce a novel cross-network collaborative application to help drive the online traffic for given videos in traditional video portal YouTube by leveraging the high propagation efficiency of the popular Twitter  ...  Vector Space Model(VSM) is used to represent the Twitter followees and target YouTube video and we select the top-k followees by sorting the cosine similarity between the TF-IDF coded vectors; • Semantic  ... 
doi:10.1109/tmm.2015.2446949 fatcat:tdjsewls6rckbli6u2qgpfs6ee

Information Systems: Towards a System of Information Systems

Majd Saleh, Marie-Hélène Abel
2015 Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management  
Due to the nature of Information Systems that revolves around creating information useful to users, and in some higher forms of Information Systems creating knowledge, management of information and/or  ...  This paper discovers what is currently known about Information Systems and Systems of Systems, and proceeds towards suggesting an architecture of a System of Information Systems that integrates several  ...  the users Twitter account. • On the right panel the user can use MEMORAe to index and store tweets semantically.  ... 
doi:10.5220/0005596101930200 dblp:conf/ic3k/SalehA15 fatcat:mbxipkdf3jao7hogyqxjtym7rm

Cognos

Saptarshi Ghosh, Naveen Sharma, Fabricio Benevenuto, Niloy Ganguly, Krishna Gummadi
2012 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12  
In this paper, we propose and investigate a new methodology for discovering topic experts in the popular Twitter social network.  ...  (List names and descriptions) provides valuable semantic cues to the experts' domain of expertise.  ...  Further, we show some examples of very recently created Twitter accounts that our hub-based crawl could discover, in Table 10 .  ... 
doi:10.1145/2348283.2348361 dblp:conf/sigir/GhoshSBGG12 fatcat:tdbotrpg3bdxjhjeoy6f32ptyi

Peddling or Creating? Investigating the Role of Twitter in News Reporting [chapter]

Ilija Subašić, Bettina Berendt
2011 Lecture Notes in Computer Science  
The results of our case study comparing Twitter and other news sources suggest that a major role of Twitter authors consists of neither creating nor peddling, but extending them by commenting on news.  ...  211 Abstract The widespread use of social media is regarded by many as the emergence of a new highway for information and news sharing promising a new informationdriven "social revolution".  ...  However, it still does not take into account the semantic difference between reports. Named-entity divergence (N D).  ... 
doi:10.1007/978-3-642-20161-5_21 fatcat:zs7wqdrvabay3mprzrvk4f4sri

Analysis and forecasting of trending topics in online media streams

Tim Althoff, Damian Borth, Jörn Hees, Andreas Dengel
2013 Proceedings of the 21st ACM international conference on Multimedia - MM '13  
Our fully automated approach is based on a nearest neighbor forecasting technique exploiting our assumption that semantically similar topics exhibit similar behavior.  ...  Our results indicate that depending on one's requirements one does not necessarily have to turn to Twitter for information about current events and that some media streams strongly emphasize content of  ...  Discovering Semantically Similar Topics. We evaluate the influence of discovering semantically similar topics in two ways.  ... 
doi:10.1145/2502081.2502117 dblp:conf/mm/AlthoffBHD13 fatcat:vuv4xfne5ncdtl6v4rvwsusymq

Analysis and Forecasting of Trending Topics in Online Media Streams [article]

Tim Althoff, Damian Borth, Jörn Hees, Andreas Dengel
2014 arXiv   pre-print
Our fully automated approach is based on a nearest neighbor forecasting technique exploiting our assumption that semantically similar topics exhibit similar behavior.  ...  Our results indicate that depending on one's requirements one does not necessarily have to turn to Twitter for information about current events and that some media streams strongly emphasize content of  ...  Discovering Semantically Similar Topics. We evaluate the influence of discovering semantically similar topics in two ways.  ... 
arXiv:1405.7452v2 fatcat:es52rjcvrjgplgxudfk5xskk4u

Inferring who-is-who in the Twitter social network

Naveen Kumar Sharma, Saptarshi Ghosh, Fabricio Benevenuto, Niloy Ganguly, Krishna Gummadi
2012 Proceedings of the 2012 ACM workshop on Workshop on online social networks - WOSN '12  
Our work provides a foundation for building better search and recommendation services on Twitter.  ...  Our key insight is that the List meta-data (names and descriptions) provides valuable semantic cues about who the users included in the Lists are, including their topics of expertise and how they are perceived  ...  A lot of prior research has focused on discovering semantic topics for web-pages.  ... 
doi:10.1145/2342549.2342563 dblp:conf/wosn/SharmaGBGG12 fatcat:gkfi6m7y2nc37nghjaq52tqepm

Inferring who-is-who in the Twitter social network

Naveen Kumar Sharma, Saptarshi Ghosh, Fabricio Benevenuto, Niloy Ganguly, Krishna Gummadi
2012 Computer communication review  
Our work provides a foundation for building better search and recommendation services on Twitter.  ...  Our key insight is that the List meta-data (names and descriptions) provides valuable semantic cues about who the users included in the Lists are, including their topics of expertise and how they are perceived  ...  A lot of prior research has focused on discovering semantic topics for web-pages.  ... 
doi:10.1145/2377677.2377782 fatcat:cbvngvdhvncrdns2q5hrmypxoe

People Opinion Topic Model

Hongxu Chen, Hongzhi Yin, Xue Li, Meng Wang, Weitong Chen, Tong Chen
2017 Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion  
., Twitter) is very useful.  ...  Experiments on real twitter dataset indicate our model is effective.  ...  EXPERIMENTS The dataset we used for experiments is collected from Twitter by using Twitter API 2 .  ... 
doi:10.1145/3041021.3051159 dblp:conf/www/ChenYLWCC17 fatcat:2abmkdto5zdgbajil4rbnvfdny

Crowdsourcing a Collective Sense of Place

Andrew Jenkins, Arie Croitoru, Andrew T. Crooks, Anthony Stefanidis, Tobias Preis
2016 PLoS ONE  
Our approach leverages probabilistic topic modelling, semantic association, and spatial clustering to find locations are conveying a collective sense of place.  ...  In this paper we present results from a novel quantitative approach to derive such sociocultural signatures from Twitter contributions and also from corresponding Wikipedia entries.  ...  The pie chart (right) shows that 13.7% of the total topics discovered from the entire NYC Twitter resulted in the highest semantic similarity with recreation out of the other five categories.  ... 
doi:10.1371/journal.pone.0152932 pmid:27050432 pmcid:PMC4822840 fatcat:7dy5y23zhfhmnjnhrjgz2q3zfu
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