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Beautiful and Damned. Combined Effect of Content Quality and Social Ties on User Engagement

Luca Maria Aiello, Rossano Schifanella, Miriam Redi, Stacey Svetlichnaya, Frank Liu, Simon Osindero
2017 IEEE Transactions on Knowledge and Data Engineering  
Beautiful images are evenly distributed in the network, although only a small core of people get social recognition for them.  ...  We develop a deep learning computer vision model to score images according to their aesthetic value and we validate its output through crowdsourcing.  ...  They developed a dynamic matched sample estimation framework to distinguish influence and homophily effects in dynamic networks, and they applied it to a global instant messaging network of 27.4 million  ... 
doi:10.1109/tkde.2017.2747552 fatcat:hnyc2psnnza6vhsp3til6khczm

Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks [article]

Xinyang Zhang, Chenwei Zhang, Luna Xin Dong, Jingbo Shang, Jiawei Han
2021 arXiv   pre-print
We therefore propose a novel framework for minimally supervised categorization by learning from the text-rich network.  ...  Such a network provides a holistic view of the corpus' heterogeneous data sources and enables a joint optimization for network-based analysis and deep textual model training.  ...  In the future, we would like to explore models that can capture heterogeneous type information in the text-rich network.  ... 
arXiv:2102.11479v1 fatcat:ji32ldzij5dn5hc4hbmbku2u4i

Systems Applications of Social Networks

Changtao Zhong, Nishanth Sastry
2017 ACM Computing Surveys  
In each case, we discuss potential directions for future research that involve using social network properties.  ...  We propose a framework, distinguishing between two main types of social network-based user selection-personalised user selection which identi es target users who may be relevant for a given source node  ...  Heterogeneity in social networks.  ... 
doi:10.1145/3092742 fatcat:hcfudmor4feonjlalyma2l6owy

A planetary nervous system for social mining and collective awareness

F. Giannotti, D. Pedreschi, A. Pentland, P. Lukowicz, D. Kossmann, J. Crowley, D. Helbing
2012 The European Physical Journal Special Topics  
mining, and the idea of trust networks and privacy-aware social mining.  ...  personal data, so that users may allow access and use of their data for their own good and the common good.  ...  The authors are indebted with many people for inspiring discussions, contributions, comments and criticisms, and remarkably: Andrzej Nowak, John Shawe- Taylor  ... 
doi:10.1140/epjst/e2012-01688-9 fatcat:4bjj4ukpzvhd5fhpt2xnf45eli

Applications of Social Media in Hydroinformatics: A Survey [article]

Yufeng Yu, Yuelong Zhu, Dingsheng Wan, Qun Zhao, Kai Shu, Huan Liu
2019 arXiv   pre-print
Floods of research and practical applications employ social media data for a wide range of public applications, including environmental monitoring, water resource managing, disaster and emergency response.Hydroinformatics  ...  means, they also make use of user's social network and related information.  ...  Moreover, it is important to know whether the underlying social network is influence driven or homophily driven because influence makes "friends become similar" while homophily makes "similar individuals  ... 
arXiv:1905.03035v1 fatcat:72ignyiinjabnk2duldns475la

Survey of Generative Methods for Social Media Analysis [article]

Stan Matwin, Aristides Milios, Paweł Prałat, Amilcar Soares, François Théberge
2021 arXiv   pre-print
We included two important aspects that currently gain importance in mining and modeling social media: dynamics and networks.  ...  This survey draws a broad-stroke, panoramic picture of the State of the Art (SoTA) of the research in generative methods for the analysis of social media data.  ...  "PC shit" [sic], where "PC" is short for "political correctness") [51] .  ... 
arXiv:2112.07041v1 fatcat:xgmduwctpbddfo67y6ack5s2um

The Impact of Digital Nudging Techniques on the Formation of Self-Assembled Crowd Project Teams

Federica Vinella, Rosa Mosch, Ioanna Lykourentzou, Judith Masthoff
2022 Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization  
In this study, we examine whether making users aware of the team's diversity can impact their selections.  ...  CCS CONCEPTS • Human-centered computing → Collaborative and social computing; Social networking sites.  ...  approaches a normal distribution, allowing for parametric tests to be used. 5000 bootstrap samples were taken; the confidence interval is bias-corrected and accelerated.  ... 
doi:10.1145/3503252.3531298 fatcat:7dlifwf66feyxd2wpr3xij7uzq

Understanding Human-Machine Networks: A Cross-Disciplinary Survey [article]

Milena Tsvetkova, Taha Yasseri, Eric T. Meyer, J. Brian Pickering, Vegard Engen, Paul Walland, Marika Lüders, Asbjørn Følstad, and George Bravos
2017 arXiv   pre-print
Such human-machine networks (HMNs) are embedded in the daily lives of people, both for personal and professional use. They can have a significant impact by producing synergy and innovations.  ...  In the current hyper-connected era, modern Information and Communication Technology systems form sophisticated networks where not only do people interact with other people, but also machines take an increasingly  ...  Nevertheless, our analytical framework remains useful for identifying specific niches for development and innovation.  ... 
arXiv:1511.05324v2 fatcat:ixawl5uo4rd5tbewgcpz3as4pm

A Survey on Trust Evaluation Based on Machine Learning

Jingwen Wang, Xuyang Jing, Zheng Yan, Yulong Fu, Witold Pedrycz, Laurence T. Yang
2020 ACM Computing Surveys  
Researchers have proposed many methods to use machine learning for trust evaluation. However, the literature still lacks a comprehensive literature review on this topic.  ...  Chen et al. [2019a] presented a trust evaluation framework for online social networks. This framework is based on machine learning and applies user features to make a trust decision.  ...  Propose a framework of trust inducing factors in social networks and use these factors to predict trust.  ... 
doi:10.1145/3408292 fatcat:fem3px673bcfdltackc7bstxji

Fusing Visual, Textual and Connectivity Clues for Studying Mental Health [article]

Amir Hossein Yazdavar, Mohammad Saeid Mahdavinejad, Goonmeet Bajaj, William Romine, Amirhassan Monadjemi, Krishnaprasad Thirunarayan, Amit Sheth, Jyotishman Pathak
2019 arXiv   pre-print
By developing a multimodal framework and employing statistical techniques for fusing heterogeneous sets of features obtained by processing visual, textual and user interaction data, we significantly enhance  ...  the current state-of-the-art approaches for identifying depressed individuals on Twitter (improving the average F1-Score by 5 percent) as well as facilitate demographic inference from social media for  ...  Multi-modal Prediction Framework We use the above findings for predicting depressive behavior.  ... 
arXiv:1902.06843v1 fatcat:kskxnzqt6jdcli5pi6tpxrpnlq

Multimodal mental health analysis in social media

Amir Hossein Yazdavar, Mohammad Saeid Mahdavinejad, Goonmeet Bajaj, William Romine, Amit Sheth, Amir Hassan Monadjemi, Krishnaprasad Thirunarayan, John M. Meddar, Annie Myers, Jyotishman Pathak, Pascal Hitzler, Jichang Zhao
2020 PLoS ONE  
By developing a multimodal framework and employing statistical techniques to fuse heterogeneous sets of features obtained through the processing of visual, textual, and user interaction data, we significantly  ...  Particularly, we examine and exploit multimodal big (social) data to discern depressive behaviors using a wide variety of features including individual-level demographics.  ...  Multi-modal prediction framework We used the above findings for predicting depressive behaviors.  ... 
doi:10.1371/journal.pone.0226248 pmid:32275658 fatcat:drijmeiiabcujnznpgeqa5zkzm

Semantically-enhanced advertisement recommender systems in social networks

Ali Pazahr, J. Javier Samper Zapater, Francisco García Sánchez, Carmen Botella, Rafael Martinez
2016 Proceedings of the 18th International Conference on Information Integration and Web-based Applications and Services - iiWAS '16  
I wish all the best for these dear people. This Thesis is included in the Spanish MINECO project ''Radio Access Technologies for Heterogeneous Wireless Networks'' (RACHEL TEC2013-47141-C4-4-R).  ...  the information with respect to client's nearness in online social frameworks, for the motivations behind information mix and trade among heterogeneous frameworks.  ...  In this paper [292] the social-based recommendation algorithms on heterogeneous social networks is investigated and proposed Hete-CF, a social collaborative filtering algorithm using heterogeneous relations  ... 
doi:10.1145/3011141.3011489 dblp:conf/iiwas/PazahrZSBM16 fatcat:oi4kf355ovhkvl3wckpzfjajsu

29th International Conference on Data Engineering [book of abstracts]

2013 2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW)  
existence of mutual neighbors, which is important for applications such as identifying network homophily.  ...  The linkage information in the existing networks can be used in conjunction with the node attribute information in both networks in order to make meaningful link recommendations.  ... 
doi:10.1109/icdew.2013.6547409 fatcat:wadzpuh3b5htli4mgb4jreoika

2020 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 31

2020 IEEE Transactions on Neural Networks and Learning Systems  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  -that appeared in this periodical during 2020, and items from previous years that were commented upon or corrected in 2020.  ...  ., +, TNNLS Dec. 2020 5349-5362 +, TNNLS March 2020 901-914 Crowdsourcing Robust Cumulative Crowdsourcing Framework Using New Incentive Payment Function and Joint Aggregation Model.  ... 
doi:10.1109/tnnls.2020.3045307 fatcat:34qoykdtarewhdscxqj5jvovqy

False Information on Web and Social Media: A Survey [article]

Srijan Kumar, Neil Shah
2018 arXiv   pre-print
In doing so, we create a unified framework to describe these recent methods and highlight a number of important directions for future research.  ...  A recent surge of research in this area has aimed to address the key issues using methods based on feature engineering, graph mining, and information modeling.  ...  We thank the authors for giving us permission to reprint their figures.  ... 
arXiv:1804.08559v1 fatcat:2qv3tigktzdnvpe37mef3mrg4a
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