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A Topological Approach for Detecting Twitter Communities with Common Interests [chapter]

Kwan Hui Lim, Amitava Datta
2013 Lecture Notes in Computer Science  
We propose an efficient topologicalbased approach for detecting communities that share common interests on Twitter.  ...  This approach is both computationally intensive and may result in communities without a common interest.  ...  Our main contributions in this chapter include the following: -An efficient topological-based approach for detecting Twitter communities comprising users that share common interests.  ... 
doi:10.1007/978-3-642-45392-2_2 fatcat:4cl4qo6wxnfrdjpk5swsvud3sy

Tweets Beget Propinquity: Detecting Highly Interactive Communities on Twitter Using Tweeting Links

Kwan Hui Lim, Amitava Datta
2012 2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology  
We propose an approach to detect highly interactive Twitter communities that share common interests, based on the frequency and patterns of direct tweeting among users, rather than the topological information  ...  From a topological aspect, we show that our method detects communities that are more cohesive and connected within different interest groups.  ...  We extend upon the Common Interest Community Detection (CICD) method [19] , [20] which is used for detecting communities comprising only individuals with common interests, using only topological links  ... 
doi:10.1109/wi-iat.2012.53 dblp:conf/webi/LimD12 fatcat:ihe5z7h6m5a5jkjpahwx4ry7bi

Survey on Community Detection in Online Social Networks

Amit Dhumal, Pravin Kamde
2015 International Journal of Computer Applications  
In this survey various community detection methods for networks with static and dynamic nature are discussed, and results of applying them on online social network is are provided.  ...  The proposed survey discusses the topic of community detection in the context of online social network.  ...  Topology based community detection Very first approach to study of various methods to identify interest of user and Twitter network properties is carried out.  ... 
doi:10.5120/21571-4609 fatcat:t76y5n62inagrdnxwskeckthqi

Finding twitter communities with common interests using following links of celebrities

Kwan Hui Lim, Amitava Datta
2012 Proceedings of the 3rd international workshop on Modeling social media - MSM '12  
We propose an efficient approach for detecting communities that share common interests on Twitter.  ...  This approach is both computationally intensive and may result in communities without a common interest.  ...  Our main contributions in this paper include the following: • An efficient approach for detecting Twitter communities that share common interest. • A study of the characteristics of Twitter communities  ... 
doi:10.1145/2310057.2310064 dblp:conf/ht/LimD12a fatcat:qy77lj6fbfaupaek5lploriwyi

Advances in FCA-based Applications for Social Networks Analysis

Marie-Aude Aufaure, Bénédicte Le Grand
2013 International Journal of Conceptual Structures and Smart Applications  
We show the benefit of FCA solutions, as well as their combination with semantics and topology-based approaches.  ...  This article presents example of successful applications of FCA for Social Networks Analysis.  ...  The association rules allow us to identify a balanced number of communities with users who share common interests.  ... 
doi:10.4018/ijcssa.2013010104 fatcat:m2lwe5tvvvd7nkqb4gxi3huwo4

Echo chamber detection and analysis

Giacomo Villa, Gabriella Pasi, Marco Viviani
2021 Social Network Analysis and Mining  
To this aim, we propose an approach based on the application of a community detection strategy to distinct topology- and content-aware representations of the COVID-19 conversation graph.  ...  AbstractSocial media allow to fulfill perceived social needs such as connecting with friends or other individuals with similar interests into virtual communities; they have also become essential as news  ...  A topology-and content-based approach for echo chamber detection and analysis The approach proposed in this work and detailed in this section, aimed at detecting and analyzing echo chambers, is framed  ... 
doi:10.1007/s13278-021-00779-3 pmid:34457082 pmcid:PMC8379609 fatcat:ho6twmkqv5fonbdpe6rveqoixm

A Biased Review of Biases in Twitter Studies on Political Collective Action [article]

Peter Cihon, Taha Yasseri
2016 arXiv   pre-print
This paper offers a minireview of Twitter-based research on political crowd behavior.  ...  This minireview considers a small number of selected papers; we analyze their (often lack of) theoretical approaches, review their methodological innovations, and offer suggestions as to the relevance  ...  The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.  ... 
arXiv:1605.04774v1 fatcat:uvnqxu7djrblhpnjmta7makjoq

A Biased Review of Biases in Twitter Studies on Political Collective Action

Peter Cihon, Taha Yasseri
2016 Frontiers in Physics  
This paper offers a minireview of Twitter-based research on political crowd behavior.  ...  This minireview considers a small number of selected papers; we analyse their (often lack of) theoretical approaches, review their methodological innovations, and offer suggestions as to the relevance  ...  ACKNOWLEDGMENTS For providing useful feedback on the original manuscript we thank Mariano Beguerisse-Díaz and Peter Grindrod.  ... 
doi:10.3389/fphy.2016.00034 fatcat:ftpl5osllba33lmsigbtwehjxe

Temporal Identification of Latent Communities on Twitter [article]

Hossein Fani, Fattane Zarrinkalam, Xin Zhao, Yue Feng, Ebrahim Bagheri, Weichang Du
2015 arXiv   pre-print
approaches for community detection.  ...  Through our experiments on Twitter data, we demonstrate i) the effectiveness of our topic detection method to detect real world topics and ii) the effectiveness of our approach compared to well-established  ...  This supports our assumption that a topology-based view to community detection on Twitter, would not necessarily be able to identify communities of users that share similar conceptual interest but do not  ... 
arXiv:1509.04227v1 fatcat:rteng5n3jffrff5wvmuuorhgjq

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

Gerasimos Razis, Ioannis Anagnostopoulos, Sherali Zeadally
2018 arXiv   pre-print
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  ...  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  ...  For example, a community detection in OSNs approach is proposed in [50] using node similarity techniques.  ... 
arXiv:1801.09961v3 fatcat:mnwvsphxgjdcvlu6vsn6g6pv5e

Advanced graph mining for community evaluation in social networks and the web

Christos Giatsidis, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2013 Proceedings of the sixth ACM international conference on Web search and data mining - WSDM '13  
A special mention is made on approaches that capitalize on the concept of degeneracy (kcores and extensions), as a novel means of community detection and evaluation.  ...  Next we offer a thorough review of fundamental methods for graph clustering and community detection, on both undirected and directed graphs.  ...  Malliaros is a recipient of the Google Europe Fellowship in Graph Mining, and this research is supported in part by this Google Fellowship.  ... 
doi:10.1145/2433396.2433495 dblp:conf/wsdm/GiatsidisMV13 fatcat:bsm3obf6zrgj5er2hc73xdpvs4

Finding interest groups from Twitter lists

Mohamed Benabdelkrim, Jean Savinien, Céline Robardet
2020 Proceedings of the 35th Annual ACM Symposium on Applied Computing  
We propose and validate a new approach that identifies local communities of users and their common interests from the constructed graph.  ...  We provide evidences that our method performs in a better way than global community detection approaches, and faster with as good results as competitive local methods.  ...  In Figure 3 , we compare patterns extracted by ExhaustiveSearch with α = 0.8 and λ = 0.8 (pink histogram) to communities returned by other methods: • Louvain: the purely topological community detection  ... 
doi:10.1145/3341105.3374077 dblp:conf/sac/BenabdelkrimSR20 fatcat:ptp7sjrgbrdelf3gjxw36h6w7q

Known by who we follow: a biclustering application to community detection

Juan M. Cotelo, F. Javier Ortega, Jose A. Troyano, Fernando Enriquez, Fermin Cruz
2020 IEEE Access  
In this paper, we address the task of detecting on-line communities of Twitter users for a given domain.  ...  Twitter, community detection, biclustering, politics. 192218 This work is licensed under a Creative Commons Attribution 4.0 License.  ...  CONCLUSION We have presented an original approach for detecting communities of interest in Twitter for a given domain.  ... 
doi:10.1109/access.2020.3032015 fatcat:phhou2tepveazk5mgoglcswgwi

The Topology of a Discussion: The #Occupy Case

Floriana Gargiulo, Jacopo Bindi, Andrea Apolloni, Daniele Marinazzo
2015 PLoS ONE  
We use a network approach based on the analysis of the bipartite graph @Users-#Hashtags and of its projections: the 'semantic network', whose nodes are hashtags, and the 'users interest network', whose  ...  nodes are users In the first instance, we find out that discussion topics (#hashtags) present a high heterogeneity, with the distinct role of the communication hubs where most the 'opinion traffic' passes  ...  Acknowledgments Floriana Gargiulo would like to thank Timoteo Carletti for the useful discussions. Andrea Apolloni would like to thank Timothy Pollington for the useful discussions.  ... 
doi:10.1371/journal.pone.0137191 pmid:26352596 pmcid:PMC4564107 fatcat:3sq6ao53g5bkdbytkffxyxha34

Detecting Fake News Spreaders in Social Networks using Inductive Representation Learning [article]

Bhavtosh Rath, Aadesh Salecha, Jaideep Srivastava
2020 arXiv   pre-print
Using topology and interaction based trust properties of nodes in real-world Twitter networks, we are able to predict false information spreaders with an accuracy of over 90%.  ...  In this paper, we propose a graph neural network based approach to identify nodes that are likely to become spreaders of false information.  ...  Figure 2 shows how we model the proposed approach with community perspective.  ... 
arXiv:2011.10817v1 fatcat:v7yt476synhspglm4526fxod5y
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