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Community Discovery from Social Media by Low-Rank Matrix Recovery

Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang
2015 ACM Transactions on Intelligent Systems and Technology  
This paper presents a novel approach to discovering communities from social media, including the group membership and user friend structure, by exploring a low-rank matrix recovery technique.  ...  Community discovery from social media has therefore become an important yet challenging issue.  ...  Community Discovery from Social Media by Low-Rank Matrix Recovery • 1:9 Table II . II The statistics about our crawled Flick dataset before (left) and after (right) pre-processing.  ... 
doi:10.1145/2668110 fatcat:to5ajfhzovhdfekf3nfqnt2zdq


Yu-Ru Lin, K. Selçcuk Candan, Hari Sundaram, Lexing Xie
2011 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
Consequently, a framework for extracting useful information from social media data needs to scale with data volume, and also with the number and diversity of the facets of the data.  ...  Social media data have three challenging characteristics.  ...  is an increasing demand for analysis frameworks that can support applications, such as community discovery, that depend on information latent in the social data [Chi et al. 2006; Kolda and Sun 2008;  ... 
doi:10.1145/2037676.2037686 fatcat:4b25ljdh6rbztjmorizls3r4ju

Scalable Interpretable Multi-Response Regression via SEED [article]

Mohammad Taha Bahadori, Zemin Zheng, Yan Liu, Jinchi Lv
2016 arXiv   pre-print
studies and social media analysis.  ...  sparse matrix by solving a sparse generalized eigenvalue problem.  ...  Sparse reduced-rank regression has found applications in micro-array biclustering (Chen et al., 2012) , subspace clustering (Wang et al., 2013) , social network community discovery (Richard et al.,  ... 
arXiv:1608.03686v1 fatcat:q5wibugdsrh2dp4l4pxva77gbe


2015 Procedia Computer Science  
Media and Real Applications Ontology-based Sentiment Analysis Process for Social Media Content P.  ...  Alimi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232 Low-Rank Tensor Recovery for Geo-Demand  ... 
doi:10.1016/s1877-0509(15)01834-7 fatcat:ighxekuqa5brdj6pa67juxrcdm

Multimedia Semantics: Interactions Between Content and Community

Hari Sundaram, Lexing Xie, Munmun De Choudhury, Yu-Ru Lin, Apostol Natsev
2012 Proceedings of the IEEE  
In this article, we study how media-rich social networks provide additional insight into familiar multimedia research problems, including tagging and video ranking.  ...  The presence of near ubiquitous low-cost computing and communication technologies have enabled people to access and share information at unprecedented scale, which necessitates new research for making  ...  The discovery of latent structure in such social media platforms can point to emergent cultural behaviors.  ... 
doi:10.1109/jproc.2012.2191529 fatcat:tayhtgkr6jfz7l2efpic4ygaqy

Community Discovery via Metagraph Factorization

Yu-Ru Lin, Jimeng Sun, Hari Sundaram, Aisling Kelliher, Paul Castro, Ravi Konuru
2011 ACM Transactions on Knowledge Discovery from Data  
The problem is particularly useful in the enterprise domain where extracting emergent community structure on enterprise social media can help in forming new collaborative teams, in expertise discovery,  ...  Extensive experiments on real-world social data collected from an enterprise and the public Digg social media website suggest that our technique is scalable and is able to extract meaningful communities  ...  Community Discovery We formalize the community discovery problem as latent space extraction from multirelational social data.  ... 
doi:10.1145/1993077.1993081 fatcat:pxfi3zt2cjdwphb4qhrfzywm5e

Joint Community and Anomaly Tracking in Dynamic Networks

Brian Baingana, Georgios B. Giannakis
2016 IEEE Transactions on Signal Processing  
By postulating edge creation as the result of mutual community participation by node pairs, a dynamic factor model with anomalous memberships captured through a sparse outlier matrix is put forth.  ...  Communities in online social networks are indicative of shared functional roles, or affiliation to a common socio-economic status, the knowledge of which is vital for targeted advertisement.  ...  Remark 2 (Sparsity and Low Rank): The estimator (8) capitalizes on sparsity and low rank properties inherent to the matrix decomposition in (4).  ... 
doi:10.1109/tsp.2015.2510971 fatcat:lg56eqa34bg27kkqact4747vn4

Recommending Users and Communities in Social Media

Lei Li, Wei Peng, Saurabh Kataria, Tong Sun, Tao Li
2015 ACM Transactions on Knowledge Discovery from Data  
Social media has become increasingly prevalent in the last few years, not only enabling people to connect with each other by social links, but also providing platforms for people to share information and  ...  In this article, we propose a unified framework of recommending users and communities that utilizes the information in social media.  ...  Naturally in social media, a community is often formed by a group of users with social connections as well as similar topic preferences.  ... 
doi:10.1145/2757282 fatcat:bm3lzlk7dres3kd5qxxgx22hhy

Link prediction via matrix completion

Ratha Pech, Dong Hao, Liming Pan, Hong Cheng, Tao Zhou
2017 Europhysics letters  
On one hand, our algorithm is based on the sparsity and low rank property of the matrix, on the other hand, it also performs very well when the network is dense.  ...  Inspired by practical importance of social networks, economic networks, biological networks and so on, studies on large and complex networks have attracted a surge of attentions in the recent years.  ...  Obviously, matrix completion can be treated as a special case of low-rank matrix recovery. Robust PCA is capable of recovering low-rank matrix in the presence of noise as defined in Eq. (5).  ... 
doi:10.1209/0295-5075/117/38002 fatcat:63mhujvsmnhyvh2fw5nw7lree4

Advances in Scaling Community Discovery Methods for Signed Graph Networks [article]

Maria Tomasso and Lucas Rusnak and Jelena Tešić
2022 arXiv   pre-print
Sign Graph Clustering, Community Discovery, Sparse Networks  ...  Community detection is a common task in social network analysis (SNA) with applications in a variety of fields including medicine, criminology, and business.  ...  In an era dominated by social media communication, the community detection tools developed specifically from social network theory can help researchers understand trends and propagation patterns within  ... 
arXiv:2110.07514v3 fatcat:uj5iridjsvevlivb3jyxvwre5e

2020 Index IEEE Transactions on Knowledge and Data Engineering Vol. 32

2021 IEEE Transactions on Knowledge and Data Engineering  
Ma, S., +, Scientific Workflow Protocol Discovery from Public Event Logs in Clouds. Fast and Low Memory Cost Matrix Factorization: Algorithm, Analysis, and Case Study.  ...  ., +, TKDE March 2020 492-505 Scientific Workflow Protocol Discovery from Public Event Logs in Clouds.  ...  Social sciences computing Discerning  ... 
doi:10.1109/tkde.2020.3038549 fatcat:75f5fmdrpjcwrasjylewyivtmu

Analysis of Resilience Priorities for Micro, Small and Medium Enterprises (MSMEs) in Deli Serdang District

Satria Tirtayasa, Januri Januri, Hazmanan Khair, R.S. Kartaatmaja
2021 Jurnal Manajemen & Agribisnis  
Dissemination and guidance on awareness using a marketing model through social media for MSME actors has an impact on changing thinking and income, and the role of all decisionmakers in obtaining information  ...  Data collection techniques in this study are secondary data collection (the income and production aspects of one-quarter of MSME during the COVID-19 pandemic which is calculated by averages and regional  ...  someone can only interact and communicate on social media if they have a set of communication tools such as computers, cellphones, laptops, tablets.Many people use social media technology several times  ... 
doi:10.17358/jma.18.2.215 fatcat:ymyi4wb7vbb55n27tgy4f2vfum

SCG: Spotting Coordinated Groups in Social Media [article]

Junhao Wang, Sacha Levy, Ren Wang, Aayushi Kulshrestha, Reihaneh Rabbany
2020 arXiv   pre-print
Recent events have led to a burgeoning awareness on the misuse of social media sites to affect political events, sway public opinion, and confuse the voters.  ...  serious, hostile mass manipulation has motivated a large body of works on bots/troll detection and fake news detection, which mostly focus on classifying at the user level based on the content generated by  ...  system through social media [28] .  ... 
arXiv:1910.07130v5 fatcat:i2f7eenpajds3cg35fb3gmwefy

2019 Index IEEE Transactions on Knowledge and Data Engineering Vol. 31

2020 IEEE Transactions on Knowledge and Data Engineering  
Pal, R., +, TKDE May 2019 965-980 Privacy-Preserving Social Media Data Publishing for Personalized Ranking-Based Recommendation.  ...  ., +, TKDE Oct. 2019 1994-2007 Modeling the Parameter Interactions in Ranking SVM with Low-Rank Approximation. Xu, J., +, TKDE June 2019 1181-1193 Multi-Label Learning from Crowds.  ... 
doi:10.1109/tkde.2019.2953412 fatcat:jkmpnsjcf5a3bhhf4ian66mj5y

Research on event perception based on geo-tagged social media data

Ruoxin Zhu, Chenyu Zuo, Diao Lin
2019 Proceedings of the ICA  
However, event study based on social media is still in its infancy. This paper provides an overview of event study based on geo-tagged social media data.  ...  How to perceive an event through social media data has triggered a series of researches. Currently, we can find when, where what happened and induced impact based on geo-tagged social media data.  ...  Geo-tagged social media data with citizens as social sensors The innovation of internet communication technology in the last decades have changed the way citizens communicate.  ... 
doi:10.5194/ica-proc-2-157-2019 fatcat:i2vo6okebvfgjl5xuiid235a3m
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