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Identifying influential scholars in academic social media platforms

Na Li, Denis Gillet
2013 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13  
The rich data collected in social media platforms has provided new opportunities for assessing scholars' impact other than the traditional citation-based approach.  ...  In this paper, we investigate the measures of scholars' influence in academic social media platforms, taking both academic and social impact into account.  ...  After that, we use a topic model [21] to analyze the text and generate topic vectors for the papers.  ... 
doi:10.1145/2492517.2492614 dblp:conf/asunam/LiG13 fatcat:5hhbjztejnb7lfco3ipdacq6tu

Web 2.0 Mining [chapter]

Anupam Joshi, Tim Finin, Akshay Java, Anubhav Kale, Pranam Kolari
2008 Chapman & Hall/CRC Data Mining and Knowledge Discovery Series  
We describe recent work on building systems that analyse these emerging social media systems to recognize spam blogs, find opinions on topics, identify communities of interest, derive trust relationships  ...  , and detect influential bloggers.  ...  James Mayfield, Justin Martineau and Sandeep Balijepalli for their contributions to the work on sentiment detection, and Amit Karandikar for his work on the generative model.  ... 
doi:10.1201/9781420085877.pt3 fatcat:oaih5n2iuve7vd3kstrql2vzpe

How do you perceive this author? Understanding and modeling authors' communication quality in social media

Kyungsik Han, Sergi Lozano
2018 PLoS ONE  
In addition, based on the author and message characteristics, we demonstrate the potential for building accurate models that can indicate an author's communication quality.  ...  In this study, we leverage human evaluations, content analysis, and computational modeling to generate a comprehensive analysis of readers' evaluations of authors' communication quality in social media  ...  Frequent use may lead readers to have more critical standpoints toward content and authors in social media.  ... 
doi:10.1371/journal.pone.0192061 pmid:29389979 pmcid:PMC5794137 fatcat:b6kwhlmv2vfehdcvsxiymfs4hq

A survey of Big Data dimensions vs Social Networks analysis

Michele Ianni, Elio Masciari, Giancarlo Sperlí
2020 Journal of Intelligent Information Systems  
The pervasive diffusion of Social Networks (SN) produced an unprecedented amount of heterogeneous data.  ...  This survey will focus on the analyses performed in last two decades on these kind of data w.r.t. the dimensions defined for Big Data paradigm (the so called Big Data 6 V's).  ...  Fang et al. (2014) desigend a Topic-sensitive influencer mining (TSIM) by using an hypergraph learning in interest-based social media networks.  ... 
doi:10.1007/s10844-020-00629-2 pmid:33191981 pmcid:PMC7649712 fatcat:3hvd5sshwzd67lxi4qlo2sgnwe

SocialSensor

Sotiris Diplaris, Symeon Papadopoulos, Ioannis Kompatsiaris, Ayse Goker, Andrew Macfarlane, Jochen Spangenberg, Hakim Hacid, Linas Maknavicius, Matthias Klusch
2012 Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion  
For example, SocialSensor will analyse the dynamic and massive user contributions in order to extract unbiased trending topics and events and will use social connections for improved recommendations.  ...  Through the proposed DySCOs-centered media search, SocialSensor will integrate social content mining, search and intelligent presentation in a personalized, context and network-aware way, based on aggregation  ...  In order to illustrate the calculation, an influence dashboard is developed which provides specific characteristics of social network users: their general influence, their specific influence per topic,  ... 
doi:10.1145/2187980.2188020 dblp:conf/www/DiplarisPKGMSHMK12 fatcat:4s3gsna5qzaulat2o52kab3pca

Redefining Media Agendas: Topic Problematization in Online Reader Comments

Olessia Koltsova, Oleg Nagornyy
2019 Media and Communication  
Based on a dataset of 33,877 news items and 258,121 comments from a sample of regional Russian newspapers we investigate readers' perceptions of social problems.  ...  It is also positively related to topic importance for the audience.  ...  Acknowledgments This article is an output of a research project implemented as part of the Basic Research Program at the National Research University Higher School of Economics (HSE University).  ... 
doi:10.17645/mac.v7i3.1894 fatcat:qhvpx6kikfhixli5ss4zoar7la

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  
This survey contains an overview of the past and recent advances in both spam detection and opinion leader identification studies in social networks.  ...  As far as we know there is no survey that contains approaches for both spam detection and opinion leader identification in 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

Novel Tools for the Management, Representation, and Exploitation of Textual Information

David Ruano-Ordás, Jose R. Méndez, Vítor Basto Fernandes, Guillermo Suárez-Tangil
2021 Scientific Programming  
We would also like to thank all authors for their contributions to this special issue and the reviewers for their generous time in providing detailed comments and suggestions that helped us to improve  ...  Content-Based Spam Filtering, TIN2017-84658-C2-1-R).  ...  media forums to automatically detect healthcare issues in patients.  ... 
doi:10.1155/2021/9781923 doaj:22bffababb7f49b79560f0b6f69dacc0 fatcat:m7hmq2stnbcvpnywvefrxyvq5q

The Information Ecology of Social Media and Online Communities

Tim Finin, Anupam Joshi, Pranam Kolari, Akshay Java, Anubhav Kale, Amit Karandikar
2008 The AI Magazine  
We describe recent work on building systems that use models of the Blogosphere to recognize spam blogs, find opinions on topics, identify communities of interest, derive trust relationships, and detect  ...  Social media systems such as weblogs, photo- and link-sharing sites, Wikis and on-line forums are currently thought to produce up to one third of new Web content.  ...  James Mayfield, Justin Martineau and Sandeep Balijepalli for their contributions to the work on sentiment detection.  ... 
doi:10.1609/aimag.v29i3.2158 fatcat:qmuzv4t7gba5vmaic3nzzfldna

Automated identification of media bias in news articles: an interdisciplinary literature review

Felix Hamborg, Karsten Donnay, Bela Gipp
2018 International Journal on Digital Libraries  
Computer science research on media bias thus stands to profit from a closer integration of models for the study of media bias developed in the social sciences with automated methods from computer science  ...  In the social sciences, research over the past decades has developed comprehensive models to describe media bias and effective, yet often manual and thus cumbersome, methods for analysis.  ...  We thank the anonymous reviewers for their valuable comments that significantly helped to improve this article.  ... 
doi:10.1007/s00799-018-0261-y fatcat:i2wdwvf5c5corl44syg2maahgm

Mining Media Topics Perceived as Social Problems by Online Audiences: Use of a Data Mining Approach in Sociology

Oleg Nagornyy, Olessia Koltsova
2017 Social Science Research Network  
We start from viewing social problem as a complex discursive phenomenon that emerges and develops in public arenas in an interplay of efforts of interest groups, media professionals, lay media and internet  ...  In this paper we show how communication scholars can benefit from using data mining methods combined with qualitative manual analysis of texts for the goal of detecting social problems via user content  ...  As mentioned above, an indicator of a topic being a social problem is its negative perception by the readers or framing by the text authors.  ... 
doi:10.2139/ssrn.2968359 fatcat:yxnlhfdy5vfsrpzsejmuamgpqe

The Misinformation Era: Review on Deep Learning Approach to Fake News Detection [article]

Banura Perera
2020 figshare.com  
Wealso looked at social media handling of the fake news pandemicand identified the new pathways for future research.  ...  Through that we have identifiedsome research gaps that we presented in this paper.  ...  In a paper [10] published in 2017, proposed detection models for social media which combat against the fake news through multiple models.These models are Knowledge-based model which is a model based  ... 
doi:10.6084/m9.figshare.13299440.v1 fatcat:mbpvpkdowfb4vaybfwokhf5pbu

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

Qixuan Hou, Meng Han, Zhipeng Cai
2020 Big Data Mining and Analytics  
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,  ...  The previous studies on information spreading, relationship analyzing, and individual modeling, etc., have been heavily conducted to explore the tremendous social and commercial values of social media  ...  [60] used data from the Location-Based Social Networks (LBSNs) and proposed a novel network model and an influence propagation model, which study influence propagation in both online social networks  ... 
doi:10.26599/bdma.2020.9020006 fatcat:msf6yz7tozbdne2mutwepo2ujy

Deciding Metrics For Detecting False News And Influence On Twitter

SHANTANU KUMAR
2017 Zenodo  
The era of the social media brings with it quite some information and news that is untrue and misleading to the masses.  ...  The purpose of this paper is to help people and industries alike, to differentiate good quality sources from bad ones based on a certain distinction of metrics and methodologies.  ...  Combining these metrics will help us find a possible user on Twitter or any other Social Media Platform, that is trying to become an influencer without really possessing the required knowledge or skills  ... 
doi:10.5281/zenodo.1420904 fatcat:c6rokwc34zgfnd56dnm4wekgyy

Ranking news events by influence decay and information fusion for media and users

Liang Kong, Shan Jiang, Rui Yan, Shize Xu, Yan Zhang
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
To the best of our knowledge, this is the first work to establish different models for computing influence decay of news topics.  ...  We notice that media focus plays an essential role in distinguishing news topics and user attention is also an important factor.  ...  . • Weak Influence(1 Point): Readers never hear the topic, or think the topic is boring. • Common Influence(2 Points): Readers know the topic, but they do not care it. • Powerful Influence(3 Points): Readers  ... 
doi:10.1145/2396761.2398530 dblp:conf/cikm/KongJYXZ12 fatcat:2ylqmovhj5dsrlitr3cuarzzci
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