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Incorporating popularity in topic models for social network analysis

Youngchul Cha, Bin Bi, Chu-Cheng Hsieh, Junghoo Cho
2013 Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '13  
However, in a social network dataset we are interested in, they correspond to popular persons (e.g., Barack Obama and Justin Bieber) and cannot be simply removed because most people are interested in them  ...  To solve this "popularity problem", we explicitly model the popularity of nodes (words) in topic models.  ...  We are also very grateful for valuable comments from the anonymous reviewers.  ... 
doi:10.1145/2484028.2484086 dblp:conf/sigir/ChaBHC13 fatcat:an2tn2l45berjl6zvgol6tajpe

Behavior analysis in social networks: Challenges, technologies, and trends

Meng Wang, Ee-Peng Lim, Lei Li, Mehmet Orgun
2016 Neurocomputing  
Acknowledgement We thank the reviewers for their great efforts. Their professional evaluations and constructive comments are vital for securing the high quality of the special issue.  ...  These papers cover widely topics related to behavior analysis in social network, including social network structure analysis, social topic analysis and behavior understanding, social user analysis, social  ...  to predict the short-term popularity of a given viral topic by using only data of historical popularity of the topic.  ... 
doi:10.1016/j.neucom.2016.06.008 fatcat:x5mumxc3orduxewwvwsdxdar54

Towards Cross-Domain Learning for Social Video Popularity Prediction

Suman Deb Roy, Tao Mei, Wenjun Zeng, Shipeng Li
2013 IEEE transactions on multimedia  
We develop a transfer learning algorithm that can learn topics from social streams allowing us to model the social prominence of video content and improve popularity predictions in the video domain.  ...  Using data comprising of 10.2 million tweets and 3.5 million YouTube videos, we show that social prominence of the video topic (context) is responsible for the sudden rise in its popularity where social  ...  based on the visibility of the media topic in online social networks.  ... 
doi:10.1109/tmm.2013.2265079 fatcat:jycldmgh7rcv7a52ii5ay7oz4i

Hierarchical Community-Level Information Diffusion Modeling in Social Networks

Yuan Zhang, Tianshu Lyu, Yan Zhang
2017 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '17  
Recently, online social networks are becoming increasingly popular platforms for social interactions.  ...  Understanding how information propagates in such networks is important for personalization and recommendation in social search.  ...  [7] apply topic models to social network analysis. Zhao et. al. [39] propose a content-based user in microblog se ings.  ... 
doi:10.1145/3077136.3080784 dblp:conf/sigir/ZhangLZ17 fatcat:ow54g76r6rcwnkrcbgciq7cmte

User-level Weibo Recommendation incorporating Social Influence based on Semi-Supervised Algorithm [article]

Daifeng Li, Zhipeng Luo, Golden Guo-zheng Sun, Jie Tang, Jingwei Zhang
2012 arXiv   pre-print
Tencent Weibo, as one of the most popular micro-blogging services in China, has attracted millions of users, producing 30-60 millions of weibo (similar as tweet in Twitter) daily.  ...  The main innovation is that we consider both direct and indirect social influence from topic level based on social balance theory.  ...  INTRODUCTION Tencent is the most popular microblogging service in China, it is an important platform combining both social media and social network, which contains 300 million users as of 2011.  ... 
arXiv:1210.7047v1 fatcat:3slglltwxffwrkzpnkjgvixtt4

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

Gerasimos Razis, Ioannis Anagnostopoulos, Sherali Zeadally
2018 arXiv   pre-print
The discovery of influential entities in all kinds of networks (e.g. social, digital, or computer) has always been an important field of study.  ...  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.  ...  Finally, the study in [97] presents a methodology for measuring social influence in mobile networks by incorporating its entropy.  ... 
arXiv:1801.09961v3 fatcat:mnwvsphxgjdcvlu6vsn6g6pv5e

Guest Editorial: Tech Mining for Engineering Management: An Introduction

Yi Zhang, Ying Huang, Denise Chiavetta, Alan L. Porter
2021 IEEE transactions on engineering management  
techniques and topic models) and/or social network analytics with bibliometrics.  ...  of similarity measurements incorporating certain popular models in text analytics, such as document embedding, semantic graph, and BM25 (for ranking features).  ... 
doi:10.1109/tem.2021.3061862 fatcat:kudqaewka5hd5p5qvq3sqqvfgy

Modeling topic specific credibility on twitter

Byungkyu Kang, John O'Donovan, Tobias Höllerer
2012 Proceedings of the 2012 ACM international conference on Intelligent User Interfaces - IUI '12  
This paper presents and evaluates three computational models for recommending credible topic-specific information in Twitter.  ...  The first model focuses on credibility at the user level, harnessing various dynamics of information flow in the underlying social graph to compute a credibility rating.  ...  ACKNOWLEDGEMENTS The authors would like to thank Cha Lee and Sibel Adali for their input on analysis methods and credibility indicators for microblogs, respectively.  ... 
doi:10.1145/2166966.2166998 dblp:conf/iui/KangOH12 fatcat:dbfqeuvgjjharn7pk5l6f4yoau

Community-based topic modeling for social tagging

Daifeng Li, Bing He, Ying Ding, Jie Tang, Cassidy Sugimoto, Zheng Qin, Erjia Yan, Juanzi Li, Tianxi Dong
2010 Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10  
The model is then applied to data from Delicious, a popular social tagging system, over the time period of 2005-2008.  ...  Exploring community is fundamental for uncovering the connections between structure and function of complex networks and for practical applications in many disciplines such as biology and sociology.  ...  INTRODUCTION Social networks have been studied for decades.  ... 
doi:10.1145/1871437.1871673 dblp:conf/cikm/LiHDTSQYLD10 fatcat:ya6zxmbudzashc2677y43v7puy

Information diffusion in online social networks

Adrien Guille, Hakim Hacid, Cecile Favre, Djamel A. Zighed
2013 SIGMOD record  
The objective is to provide a comprehensive analysis and guide of existing efforts around information diffusion in social networks.  ...  A lot of effort have been made in order to understand this phenomenon, ranging from popular topic detection to information diffusion modeling, including influential spreaders identification.  ...  related to information diffusion analysis in online social networks, ranging from popular topic detection to di↵usion modeling techniques, including methods for identifying influential spreaders.  ... 
doi:10.1145/2503792.2503797 fatcat:hdusatji55atrpxiatsetizijq

Incorporating Text Analysis into Evolution of Social Groups in Blogosphere [article]

Bogdan Gliwa, Anna Zygmunt, Stanisław Podgórski
2013 arXiv   pre-print
Method presented in this paper combine social network analysis and text mining in order to understand groups evolution.  ...  Data reflecting social and business relations has often form of network of connections between entities (called social network).  ...  Aggarwal and Wang in [14] provided broad overview of text mining methods useful for social networks analysis.  ... 
arXiv:1308.4999v1 fatcat:i3kahqh2c5flddfxy552bayllm

MICROBLOGGING CONTENT PROPAGATION MODELING USING VIRALITY AND SUSCEPTIBILITY ANALYSIS

2017 International Journal of Recent Trends in Engineering and Research  
Based on this framework, it develop a numerical factorization model and another probabilistic factorization variant. The work also develop an efficient algorithm for the models' parameters learning.  ...  In this work, we study the problem of mining these behavioral factors specific to topics from microblogging content propagation data.  ...  Topics of tweets and retweets at network level To compare the likelihood of getting retweeted across topics, in each time window and for each topic k, we derive the relative popularities of topic k among  ... 
doi:10.23883/ijrter.2017.3367.roa9k fatcat:ldtca7fprbhvpobq32efrp336a

The Highs in Communication Research: Research Topics With High Supply, High Popularity, and High Prestige in High-Impact Journals

Chung-hong Chan, Christiane Grill
2020 Communication Research  
By means of topic modeling, citation counts and citation networks, our study showcases how our approach is able to reveal the intellectual architecture of our discipline in order to identify relevant paths  ...  Tailoring for the fragmented topical landscape of communication research, we propose an integrative combination of three metrics: supply, popularity, and prestige of research topics.  ...  Citation Network Analysis All articles for which we had information on citing articles were included for the citation network analysis.  ... 
doi:10.1177/0093650220944790 fatcat:lkfi3yvs5za7jikzotqruyzmfe

Social-network analysis using topic models

Youngchul Cha, Junghoo Cho
2012 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12  
In this paper, we discuss how we can extend probabilistic topic models to analyze the relationship graph of popular social-network data, so that we can "group" or "label" the edges and nodes in the graph  ...  Our proposed methods can be used for providing, for instance, more relevant friend recommendations within a social network.  ...  In this section, we briefly review related work in social-network cluster analysis and topic-model-based social-network analysis.  ... 
doi:10.1145/2348283.2348360 dblp:conf/sigir/ChaC12 fatcat:bk5i3l7tpjfs5jonrkvflhxn3q

Modeling and predicting personal information dissemination behavior

Xiaodan Song, Ching-Yung Lin, Belle L. Tseng, Ming-Ting Sun
2005 Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining - KDD '05  
For instance, "to whom a person is going to send a specific email" can be predicted by one's personal social network and content analysis.  ...  It can be used for personal social capital management. Clusters of CommunityNets provide a view of informal networks for organization management.  ...  -let me know if you see results.…… 1) Incorporate content analysis into social network in an unsupervised way 2) Build a CommunityNet for each user to capture the context- dependent, temporal evolutionary  ... 
doi:10.1145/1081870.1081925 dblp:conf/kdd/SongLTS05 fatcat:fmibvgpvibealoklgl3advboou
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