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Community-Driven Social Influence Analysis and Applications [chapter]

Yang Zhang, Jun Pang
2015 Lecture Notes in Computer Science  
Through experiments with a location-based social networks dataset, we start by demonstrating communities' influence on users' mobility, and then we focus on the influence of leaders in the communities.  ...  In this PhD project, we aim to study users' social influence at the community level, mainly because users in social networks are naturally organized in communities and communities play fundamental roles  ...  Current Results Community Detection To study social influence at the community level, the first step would be discovering communities in a social network.  ... 
doi:10.1007/978-3-319-19890-3_48 fatcat:m27ufbm4p5holbeuw7yl4lflxu

Influence Evaluation Model of Microblog User Based on Gaussian Bayesian Derivative Classifier

Chunliang Zhou, Weipeng Zhang, Zhengqiu Lu, Xiangpei Meng, Cheng Tan, Ying Xu, Zaoli Yang
2022 Mathematical Problems in Engineering  
In order to depict the influence of Weibo user, an evaluation model is proposed with Gaussian Bayesian derivatives.  ...  At first, the influence indexes of Weibo user is presented in this model with activity degree, relation degree, and coverage degree.  ...  Event detection in social networks refers to the discovery of popular events in the micro-blog text information published or forwarded by social network users.  ... 
doi:10.1155/2022/5616445 fatcat:cnwwka36izdslme4otl57msjge

Detecting Communities of Authority and Analyzing Their Influence in Dynamic Social Networks

Belkacem Chikhaoui, Mauricio Chiazzaro, Shengrui Wang, Martin Sotir
2017 ACM Transactions on Intelligent Systems and Technology  
This article addresses the problems of detecting communities of authority and of estimating the influence of such communities in dynamic social networks.  ...  Users in real-world social networks are organized into communities that differ from each other in terms of influence, authority, interest, size, etc.  ...  To overcome this shortcoming, in this article, we propose a novel approach to detecting communities of authority in social networks and assessing the influence between them.  ... 
doi:10.1145/3070658 fatcat:psj7a4ev4jdg7m7h26xdcbryxy

A Survey of Data Mining Techniques for Social Media Analysis [article]

Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Frederic Stahl
2014 arXiv   pre-print
Social network has gained remarkable attention in the last decade.  ...  People are becoming more interested in and relying on social network for information, news and opinion of other users on diverse subject matters.  ...  Communities on social networks, like any other communities in the real world, are very complex in nature and difficult to detect.  ... 
arXiv:1312.4617v2 fatcat:7zulil64vfhrpeexj5mcs7canq

Social-based Cooperation of Vehicles for Data Dissemination of Critical Urban Events [article]

Alisson Yury, Everaldo Andrade, Michele Nogueira, Aldri Santos, Fernando Matos
2020 arXiv   pre-print
It is based on vehicles' community with common interests and/or similar routines and employs social influence of vehicles according to their network location to select relay vehicles.  ...  event data in a real-time and robust way without overloading the~network.  ...  The establishment and perception of community are two techniques of social networks employed in vehicular networks [7] .  ... 
arXiv:2009.04315v1 fatcat:4vxxz5ffvnaexd4gq7xetckqai

Event-driven TV Programs Web Community Exploration

Ruggero G. Pensa, Claudio Schifanella, Luca Vignaroli
2017 ACM Conference on Hypertext & Social Media  
understand how they affect the community structure of the social network.  ...  that allows to compute, characterize and explore dynamic social web communities.  ...  GalaxyExplorer [6] is an influence-driven visual analysis system for exploring how users influence each other in a social network.  ... 
dblp:conf/ht/PensaSV17 fatcat:qnxgyqxdkvds7f5kb6uc4dg5fy

Survey on data analysis in social media: A practical application aspect

Qixuan Hou, Meng Han, Zhipeng Cai
2020 Big Data Mining and Analytics  
Social media has more than three billion users sharing events, comments, and feelings throughout the world.  ...  We outline a commonly used pipeline in building social media-based applications and focus on discussing available analysis techniques, such as topic analysis, time series analysis, sentiment analysis,  ...  Influencers are rare in social networks, but their influence can quickly spread to most nodes in the network.  ... 
doi:10.26599/bdma.2020.9020006 fatcat:msf6yz7tozbdne2mutwepo2ujy

A Survey of Data Mining Techniques for Internet

Aishwarya Lakshmi R, SashiKumar D R
2017 International Journal of Advanced Research in Computer Science and Software Engineering  
Social network has gained remarkable attention in the last decade.  ...  People are becoming more interested in and relying on social network for information, news and opinion of other users on diverse subject matters.  ...  Communities on social networks, like any other communities in the real world, are very complex in nature and difficult to detect.  ... 
doi:10.23956/ijarcsse/v7i1/0125 fatcat:wdtrh5du7ja3tkby5qoc7gmplm

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  ...  The discovery of influential entities in all kinds of networks (e.g. social, digital, or computer) has always been an important field of study.  ...  , event detection, product marketing). • Topic 3 -Community Detection: This category covers works that use social semantics for the detection of communities in OSNs.  ... 
arXiv:1801.09961v3 fatcat:mnwvsphxgjdcvlu6vsn6g6pv5e

Exploring Social Relationships in Text Streams

Ye Wang
2016 EAI Endorsed Transactions on Scalable Information Systems  
Most raw information related to social relationships are continuously generated by social networks in a form of text, for the reason that it has the lowest storage consumption while still possesses powerful  ...  Its applications can be seen in various scenarios ranging from market planning, fraud detection to the protection of national security.  ...  Next, event evolution will be modelled and analysed in a view that resembles physical field, where public opinions are regarded as forces that have visible influences in social networks.  ... 
doi:10.4108/eai.9-8-2016.151631 fatcat:oacil33o55fpdla722dyanjjoe

Overlapping Social Network Communities and Viral Marketing

Sajid Yousuf Bhat, Muhammad Abulaish
2013 2013 International Symposium on Computational and Business Intelligence  
This paper aims to present the importance of identifying overlapping communities for the task of viral marketing in social networks and also provides some experimental results on an email network to back  ...  1 Social networks have highly been used to understand the behavior and activities of individuals in nature and society.  ...  In this regard, Bhat and Abulaish [1] proposed a density-based overlapping community detection method to track the evolution of overlapping communities in dynamic social networks.  ... 
doi:10.1109/iscbi.2013.56 fatcat:eofmjp5c5va6baeyk6xrugxhri

Event Detection and Multi-source Propagation for Online Social Network Management

Lei-lei Shi, Lu Liu, Yan Wu, Liang Jiang, Ayodeji Ayorinde
2019 Journal of Network and Systems Management  
of users and information characteristics in the process of communication and network management.  ...  The social network is a huge source of information, which plays an increasingly crucial role in people's daily lives.  ...  in social networks in a more realistic way.  ... 
doi:10.1007/s10922-019-09493-0 fatcat:scts72mmnvfhjml45mifor4bxm

Modeling Implicit Communities using Spatio-Temporal Point Processes from Geo-tagged Event Traces [article]

Ankita Likhyani and Vinayak Gupta and Srijith P. K. and Deepak P. and Srikanta Bedathur
2020 arXiv   pre-print
but discrete space of locations that simultaneously models the implicit communities of users based on their check-in activities, without making use of their social network connections.  ...  In this paper, we focus on the problem of community detection as well as capturing the underlying diffusion process and propose a model COLAB based on Spatio-temporal point processes in continuous time  ...  Point processes [6] , which are popular models for sequential and temporal data, have been recently explored for community detection in general social networks [29] .  ... 
arXiv:2006.07580v1 fatcat:ep4zgc2iw5bjvetkl2gbfpkabi

Correlation analysis of community detection in social network of big data methodical using set theorem

K M. Monica, R Parvathi
2018 International Journal of Engineering & Technology  
A trending issue in the network system that aids in learning and understanding the overall network structure is the community detection in the social network.  ...  In addition to this, several basic concepts are stated in an exhaustive way where the research fields arise from social networks.  ...  A novel algorithm for community detection and influence ranking in social networks An inherent fact of influence-based connectivity and proximity encoded in the network topology has been developed and  ... 
doi:10.14419/ijet.v7i2.21.12451 fatcat:gtp5jy2uyzab7flr6zhttqxg5a

Literature Survey on Interplay of Topics, Information Diffusion and Connections on Social Networks [article]

Kuntal Dey, Saroj Kaushik, L. Venkata Subramaniam
2017 arXiv   pre-print
They have investigated the role of content, social connections and communities, familiarity and behavioral similarity in this context.  ...  Researchers have attempted to model information diffusion and topic trends and lifecycle on online social networks.  ...  Topic-Based Community Discovery In the social network analysis literature, communities are identified by one of the following.  ... 
arXiv:1706.00921v1 fatcat:doqorr3v2zhq5oiemm5zhlmc3u
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