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Topic-oriented community detection of rating-based social networks

Ali Reihanian, Behrouz Minaei-Bidgoli, Hosein Alizadeh
2016 Journal of King Saud University: Computer and Information Sciences  
In this research, the effect of topic analysis in finding more meaningful communities in social networking sites in which the users express their feelings toward different objects (like movies) by means  ...  Most of the researches in the field of community detection mainly focus on the topological structure of the network without performing any content analysis.  ...  In order to evaluate the effect of topic consideration in identifying communities of rating-based social networks, extensive experiments are conducted on real-life data sets.  ... 
doi:10.1016/j.jksuci.2015.07.001 fatcat:bhhles57z5a75mbt5fuj3kxjhy

Towards Finding Valuable Topics [chapter]

Zhen Wen, Ching-Yung Lin
2010 Proceedings of the 2010 SIAM International Conference on Data Mining  
For the second question, we identify and evaluate a set of significant factors including both content and social network factors.  ...  In particular, the social network factors are better in filtering out low-value topics, while content factors are more effective in selecting a few top high-value topics.  ...  preliminary subjective topic evaluation: (4.11) u(N ) = N j=1 rating j T j=1 rating j where rating j is the human rating of the j-th topic.  ... 
doi:10.1137/1.9781611972801.63 dblp:conf/sdm/WenL10 fatcat:erq5266xczb4hekhjmclmkub5q

SocialTrust++: Building community-based trust in Social Information Systems

James Caverlee, Zhiyuan Cheng, Brian Eoff, Chiao-Fang Hsu, Krishna Kamath, Said Kashoob, Jeremy Kelley, Elham Khabiri, Kyumin Lee
2010 Proceedings of the 6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing  
Concretely, we are developing a trustworthy community-based information platform so that each user in a Social Information System can have transparent access to the community's trust perspective to enable  ...  more effective and efficient social information access.  ...  These trust groups can serve as the basis for community trust building and guide the development of more effective community-based information exploration in social systems.  ... 
doi:10.4108/icst.collaboratecom.2010.40 dblp:conf/colcom/CaverleeCEHKKKKL10 fatcat:t6dytjhuljb65gf43s2dtralze

Sosyal Ağlarda Topluluk ve Konu Tespiti: Bir Sistematik Literatür Taraması
Systematic Literature Review of Detecting Topics and Communities in Social Networks

Ömer Ayberk ŞENCAN, İsmail ATACAK, İbrahim DOGRU
2022 Bilişim Teknolojileri Dergisi  
Therefore, it is vital for researchers to conduct research on topic detection and community detection research areas in social networks and to develop methods and techniques for problem-solving.  ...  In this study, a systematic and in-depth literature review is provided on studies that conduct topic and community analysis on social media platforms to provide a comprehensive overview of the given areas  ...  Community detection aims to identify compatible clusters or groups in real-world graphs, such as social media networks [2] . It also aims to identify the modules of the graph as well [3] .  ... 
doi:10.17671/gazibtd.1061332 fatcat:43ujcu5dgzaqtktokzumfkhh2u

A Normalized Rich-Club Connectivity-Based Strategy for Keyword Selection in Social Media Analysis

Ying Lian, Xiaofeng Lin, Xuefan Dong, Shengjie Hou
2022 Sustainability  
In this paper, we present a study on keyword selection behavior in social media analysis that is focused on particular topics, and propose a new effective strategy that considers the co-occurrence relationships  ...  The empirical results based on four topics and comparing four existing models confirm the performance of our proposed strategy in promoting the quantity and ensuing the quality of data related to particular  ...  Acknowledgments: The authors thank the reviewers for their useful discussions and comments on this manuscript.  ... 
doi:10.3390/su14137722 fatcat:njisiltghreaxejzy2ibsgjczq

A Connection-Centric Survey of Recommender Systems Research [article]

Saverio Perugini, Marcos Andre Goncalves, Edward A. Fox
2003 arXiv   pre-print
While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own.  ...  Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context.  ...  In addition, we thank him for feedback regarding initial drafts of this survey. Furthermore, discussion summaries and feedback from those in CS6604 improved the organization of this paper.  ... 
arXiv:cs/0205059v2 fatcat:t45q7wvdmrg3badt2ioeagwasa

Recommender Systems Research: A Connection-Centric Survey

Saverio Perugini, Marcos André Gonçalves, Edward A. Fox
2004 Journal of Intelligent Information Systems  
A connection-centric view of recommendation as bringing people together into a social network (center). (left) Formation of a social network by explicitly collecting ratings or profiles.  ...  (right) Identification and discovery of a network by exposing self-organizing communities implicit in user-generated data such as communication or web logs.  ...  In addition, we thank him for feedback regarding initial drafts of this survey. Furthermore, discussion summaries and feedback from those in CS6604 improved the organization of this paper.  ... 
doi:10.1023/b:jiis.0000039532.05533.99 fatcat:rscxs4oypfffpkvkbntzz4xnx4

Exploit Social Relations in Sentiment Analysis of Social Media Content for Disaster Management

Pratik Shivarkar, Wei Wei
2018 Americas Conference on Information Systems  
We propose to augment the effectiveness of such analysis by incorporating social relations in sentiment classification models.  ...  The world has witnessed the prevailing usage of social media for communication during disasters.  ...  Both studies used Twitter data, taking into consideration of the user-user networks formed on Twitter.  ... 
dblp:conf/amcis/ShivarkarW18 fatcat:ahb5a5e6izfmloygd4c5jtmwkm

Assessment of Effectiveness of Content Models for Approximating Twitter Social Connection Structures [article]

Kuntal Dey and Sahil Agrawal and Rahul Malviya and Saroj Kaushik
2016 arXiv   pre-print
Unigram, bigram and LDA content models were empirically investigated for evaluation of effectiveness, as approximators of underlying social graphs, such that they maintain the community social property  ...  We examined the overlap of the community structures of the constructed graphs, and followership-based social communities, to find the social goodness of the links constructed.  ...  social graph of user-pairs, using Twitter followership graph 15: identify BGLL communities in the topic-level social graph 16: find topic-level goodness value by finding NMI of language and social  ... 
arXiv:1605.09338v2 fatcat:2qpcvdu5arbwbbl2xkmharp2dq

Natural Language Processing via LDA Topic Model in Recommendation Systems [article]

Hamed Jelodar, Yongli Wang, Mahdi Rabbani, SeyedValyAllah Ayobi
2019 arXiv   pre-print
Our study suggest that the recommendation systems based on LDA could be effective in building smart recommendation system in online communities.  ...  Today, Internet is one of the widest available media worldwide.  ...  In terms of achieving an effective recommendation, CF approach requires either ratings on an item or a large number of ratings from a user.  ... 
arXiv:1909.09551v1 fatcat:ok3piccvx5agfds6adyiny2aom

Human judgments in hiring decisions based on online social network profiles

Yoram Bachrach
2015 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA)  
Online social networks have changed the ways in which people communicate and interact, and have also impacted the business landscape.  ...  Our results are based on datasets consisting of reports of participants who actually took part in a task of evaluating candidates.  ...  Our results in the previous section indicate that the above factors are predictive of candidate ratings when evaluating them by their social network profiles.  ... 
doi:10.1109/dsaa.2015.7344842 dblp:conf/dsaa/Bachrach15 fatcat:gwycxb744fclbg3zeumpccdjby

From past to present: Spam detection and identifying opinion leaders in social networks

Ayşe Berna ALTINEL GİRGİN
2022 Sigma Journal of Engineering and Natural Sciences  
Thanks to the rapid flow of information in social networks, it can reach millions of people in seconds.  ...  Since the information in social networks became accessible, research started to be conducted using the information on the social networks.  ...  Points of view in this document are those of the authors and do not necessarily represent the official position or policies of TÜBİTAK.  ... 
doi:10.14744/sigma.2022.00043 fatcat:56yfrjlxfzav7mnfgbfxpsxcyq

Editorial - Volume 17, Issue 6

Rory McGreal
2016 International Review of Research in Open and Distance Learning  
This theme is followed by one of interaction and social networking with papers on the  ...  to the OER effects on student progress in higher education, including how faculty members act when adopting OER. Open assessment is also covered, segueing into the evaluation of virtual objects.  ...  In their paper, Chiappe, Pinto, and Arias conducted a meta-synthesis of more than 100 studies on ICT-based assessment, identifying common topics.  ... 
doi:10.19173/irrodl.v17i6.3090 fatcat:3f4r4dsrzrestaniese6h2jlly

Analysis of User Network and Correlation for Community Discovery Based on Topic-Aware Similarity and Behavioral Influence

Xiaokang Zhou, Bo Wu, Qun Jin
2017 IEEE Transactions on Human-Machine Systems  
The dynamically socialized user networking (DSUN) model is extended and refined to represent implicit and explicit user relationships in terms of topic-aware features and social behaviors.  ...  Comparison with six different schemes and two existing methods demonstrates that the proposed method is effective in discovering influence-based communities.  ...  For the first author, part of this work was conducted for his Ph.D. thesis at Waseda University.  ... 
doi:10.1109/thms.2017.2725341 fatcat:p2so5cr5cvhszfoz6gsu5trtpq

Socirank – Identifying and Ranking Prevent News Topics Using Social Media Factors

2018 International Journal of Recent Trends in Engineering and Research  
Second, the fleeting predominance of the theme in social media demonstrates its client consideration (UA).  ...  Last, the communication between the internet based life clients who notice this theme demonstrates the quality of the network talking about it, and can be viewed as the client connection (UI) around the  ...  an unsupervised systemSociRankwhich effectively identifies news topics that are prevalent in both social media and the news media, and then ranks them by relevance using their degrees of MF, UA, and UI  ... 
doi:10.23883/ijrter.2018.4238.mkvd0 fatcat:mtonegibq5cgpjx5kryt44rhzq
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