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Exploiting Popularity and Similarity for Link Recommendation in Twitter Networks

Jun Zou, Faramarz Fekri
2014 ACM Conference on Recommender Systems  
In this paper, we propose two approaches to exploiting both popularity and similarity for link recommendation.  ...  Both popularity and similarity are important factors that drive the growth of the Twitter network.  ...  In this paper, we compare various popularitybased algorithms and similarity-based algorithms for Twitter user recommendation, and propose two approaches to exploiting both popularity and similarity.  ... 
dblp:conf/recsys/ZouF14 fatcat:4o7hqnauivcttjag7pyzs656dq

Understanding users Display-Name Consistency across Social Networks

2019 International Journal of Engineering and Advanced Technology  
As different social networking services acquire common personal attributes of the same user and present them in a variety of formats.  ...  display-name similarity across social networks.  ...  But in the current scenario, both types of information are the main concern for user privacy and most of the social media sites recommend a new friend with the friendship recommendation method.  ... 
doi:10.35940/ijeat.e1098.0785s319 fatcat:xadi6bdzorhkxhz3evxkabjeei

Understanding the Users Personal Attributes Similarity Across Online Social Networks

a user, which will further help us to improve recommendations and analyze for criminal behavior and similar applications.  ...  This study provides an analysis of the typical variations in names and usernames, which can further be studied for the extension to other social networks This profile will help in behavior analysis of  ...  These findings can be exploited in users' behavior analysis, which will further help in improving social recommendation system for the creation of customized and novel online services.  ... 
doi:10.35940/ijitee.k1297.0981119 fatcat:w7mjkgk375h73mowuiartc7q3i

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

Gerasimos Razis, Ioannis Anagnostopoulos, Sherali Zeadally
2018 arXiv   pre-print
In recent years, Online Social Networks (OSNs) have been established as a basic means of communication and often influencers and opinion makers promote politics, events, brands or products through viral  ...  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.  ...  The framework in [32] exploits common vocabularies and Linked Data in order to extract microblogging data regarding scientific events from Twitter.  ... 
arXiv:1801.09961v3 fatcat:mnwvsphxgjdcvlu6vsn6g6pv5e

Network-Aware Recommendations of Novel Tweets

Noor Aldeen Alawad, Aris Anagnostopoulos, Stefano Leonardi, Ida Mele, Fabrizio Silvestri
2016 Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval - SIGIR '16  
In this paper, we present a novel tweet-recommendation approach, which exploits network, content, and retweet analyses for making recommendations of tweets.  ...  To do that, we create the user's ego-network up to depth two and apply the transitivity property of the friendsof-friends relationship to determine interesting recommendations, which are then ranked to  ...  Acknowledgement We would like to thank the authors of [10] for having provided the code of their recommendation algorithm.  ... 
doi:10.1145/2911451.2914760 dblp:conf/sigir/AlawadALMS16 fatcat:34alhvjuqjf3zkax6ef24ersaq

From chatter to headlines

Gianmarco De Francisci Morales, Aristides Gionis, Claudio Lucchese
2012 Proceedings of the fifth ACM international conference on Web search and data mining - WSDM '12  
We propose a new methodology for recommending interesting news to users by exploiting the information in their twitter persona.  ...  stream, and topic popularity in the news and in the whole twitter-land.  ...  2 Due to its popularity, traditional news providers, such as magazines, news agencies, have become twitter users: they exploit twitter and its social network to disseminate their contents.  ... 
doi:10.1145/2124295.2124315 dblp:conf/wsdm/MoralesGL12 fatcat:6bkgdiirkbceziko243frivooa

Predicting Swedish Elections with Twitter

Nima Dokoohaki, Filippia Zikou, Daniel Gillblad, Mihhail Matskin
2015 Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15  
By distinguishing between member and official party accounts, we report that even using a focuscrawled public dataset, structural link popularities bear strong statistical similarities with vote outcomes  ...  In addition we report strong ranked dependence between standings of selected politicians and general election outcome, as well as for official party accounts and European election outcome.  ...  Zou and Fekri [22] propose two approaches to exploiting both popularity and similarity for link recommendation.  ... 
doi:10.1145/2808797.2808915 dblp:conf/asunam/DokoohakiZGM15 fatcat:qovz55tcp5f2venbbrchgfvmy4

Social Information Retrieval and Recommendation: state- of-the-art and future research
Recherche d'Information Sociale et Recommandation: Etat d'art et travaux futurs

Abir Gorrab, Ferihane Kboubi, Henda Ghézala
2019 ARIMA  
The explosion of web 2.0 and social networks has created an enormous and rewarding source of information that has motivated researchers in different fields to exploit it.  ...  and recommendation.  ...  It calculates the similarity taking into account the direct and indirect links in a graph.  ... 
doi:10.46298/arima.3101 fatcat:vivbuko5ffee3bxemhazqn3siy

Linking Accounts across Social Networks: the Case of StackOverflow, Github and Twitter

Giuseppe Silvestri, Jie Yang, Alessandro Bozzon, Andrea Tagarelli
2015 International Workshop on Knowledge Discovery on the Web  
By exploiting user attributes, platform-specific services, and different matching strategies, this paper contributes a methodology for linking user accounts across StackOverflow, Github and Twitter.  ...  We show how tens of thousands of accounts in StackOverflow, Github, and Twitter could be successfully linked.  ...  Similarly in Github and Twitter, in-degree distribution is more skewed than out-degree distribution, indicating that a small number of users are highly popular in the network.  ... 
dblp:conf/kdweb/SilvestriYBT15 fatcat:nr5nge7kkrfabe542ui27cp5ve

Finding Nemo: Searching and Resolving Identities of Users Across Online Social Networks [article]

Paridhi Jain, Ponnurangam Kumaraguru
2012 arXiv   pre-print
We test our system on two most popular and distinct social networks - Twitter and Facebook. We show that the integrated system gives better accuracy than the individual algorithms.  ...  The system exploits a known identity on one social network to search for her identities on other social networks.  ...  We test our algorithms and the system on two most popular and distinct social networks -Twitter and Facebook.  ... 
arXiv:1212.6147v1 fatcat:adt5vid5zncrxe7qx6s6to4z6i

Unified YouTube Video Recommendation via Cross-network Collaboration

Ming Yan, Jitao Sang, Changsheng Xu
2015 Proceedings of the 5th ACM on International Conference on Multimedia Retrieval - ICMR '15  
In this paper, we propose a unified YouTube video recommendation solution via cross-network collaboration: users' auxiliary information on Twitter are exploited to address the typical problems in single  ...  Experimental results show that the proposed cross-network collaborative solution achieves superior performance not only in term of accuracy, but also in improving the diversity and novelty of the recommended  ...  This shows the advantage of cross-network collaborative recommendation in exploiting users' versatile interests in different domains and the potentials in serendipity recommendation.  ... 
doi:10.1145/2671188.2749344 dblp:conf/mir/YanSX15 fatcat:p4rtjokbsnd2fdvwh4zrq7jqli

Tracking the History and Evolution of Entities: Entity-centric Temporal Analysis of Large Social Media Archives [article]

Pavlos Fafalios, Vasileios Iosifidis, Kostas Stefanidis, Eirini Ntoutsi
2018 arXiv   pre-print
In particular, user-generated content posted in social networks, like Twitter and Facebook, can be seen as a comprehensive documentation of our society, and thus meaningful analysis methods over such archived  ...  data are of immense value for sociologists, historians and other interested parties who want to study the history and evolution of entities and events.  ...  Acknowledgements The work was partially funded by the European Commission for the ERC Advanced Grant ALEXANDRIA (No. 339233) and by the German Research Foundation (DFG) project OSCAR (Opinion Stream Classification  ... 
arXiv:1810.11017v1 fatcat:44ts5exkqjdjhgh7angappl6t4

A personalized recommender system for pervasive social networks

Valerio Arnaboldi, Mattia G. Campana, Franca Delmastro, Elena Pagani
2017 Pervasive and Mobile Computing  
In this work we propose a novel framework for pervasive social networks, called Pervasive PLIERS (pPLIERS), able to discover and select, in a highly personalized way, contents of interest for single mobile  ...  For each scenario, we used real or synthetic mobility traces and we extracted real datasets from Twitter interactions to characterise the generation and sharing of user contents.  ...  In this way, the recommender system exploits the structure of the graph to identify content relevant for the user.  ... 
doi:10.1016/j.pmcj.2016.08.010 fatcat:coegf4tv3na3pg7fnxlrb3jjdm

Think Twice before You Share: Analyzing Privacy Leakage under Privacy Control in Online Social Networks [chapter]

Yan Li, Yingjiu Li, Qiang Yan, Robert H. Deng
2013 Lecture Notes in Computer Science  
Online Social Networks (OSNs) have become one of the major platforms for social interactions. Privacy control is deployed in popular OSNs to protect user's data.  ...  By examining typical OSNs including Facebook, Google+, and Twitter, we discover a series of privacy exploits which are caused by the conflicts between privacy control and OSN functionalities.  ...  This research is supported by the Singapore National Research Foundation under its International Research Centre @ Singapore Funding Initiative and administered by the IDM Programme Office.  ... 
doi:10.1007/978-3-642-38631-2_55 fatcat:yf62vzdy5belfgjc2j6n54d2qu

@i seek ''

Paridhi Jain, Ponnurangam Kumaraguru, Anupam Joshi
2013 Proceedings of the 22nd International Conference on World Wide Web - WWW '13 Companion  
In this work, we introduce two novel identity search algorithms based on content and network attributes and improve on traditional identity search algorithm based on profile attributes of a user.  ...  for only 27.4%.  ...  Special thanks to Anshu Malhotra and Luam Totti for sharing the dataset and Siddhartha Asthana for his feedback during the development of this paper.  ... 
doi:10.1145/2487788.2488160 dblp:conf/www/JainKJ13 fatcat:yftulovtnfcwpl4b5dfpcoig2q
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