research-article

Predicting citations from mainstream news, weblogs and discussion forums

Authors:

Mohan Timilsina,

Conor HayesAuthors Info & Claims

WI '17: Proceedings of the International Conference on Web Intelligence

Pages 237 - 244

https://doi.org/10.1145/3106426.3106450

Published: 23 August 2017 Publication History

Abstract

The growth in the alternative digital publishing is widening the breadth of scholarly impact beyond the conventional bibliometric community. Thus, research is becoming more reachable both inside and outside of academic institutions and are found to be shared, downloaded and discussed in social media. In this study, we linked the scientific articles found in mainstream news, weblogs and Stack Overflow to the citation database of peer-reviewed literature called Scopus. We then explored how standard graph-based influence metrics can be used to measure the social impact of scientific articles. We also proposed the variant of Katz centrality metrics called EgoMet score to measure the local importance of scientific articles in its ego network. Later we evaluated these computed graph-based influence metrics by predicting absolute citations. Our results of the prediction model describe 34% variance to predict citations from blogs and mainstream news and 44% variance to predict citations from Stack Overflow.

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Cited By

Timilsina MFigueroa A(2023)Neural age screening on question answering communitiesEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.106219123(106219)Online publication date: Aug-2023
https://doi.org/10.1016/j.engappai.2023.106219
Figueroa ATimilsina M(2021)What identifies different age cohorts in Yahoo! Answers?Knowledge-Based Systems10.1016/j.knosys.2021.107278(107278)Online publication date: Jul-2021
https://doi.org/10.1016/j.knosys.2021.107278
Akella AAlhoori HKondamudi PFreeman CZhou H(2021)Early indicators of scientific impact: Predicting citations with altmetricsJournal of Informetrics10.1016/j.joi.2020.10112815:2(101128)Online publication date: May-2021
https://doi.org/10.1016/j.joi.2020.101128
Show More Cited By

Index Terms

Predicting citations from mainstream news, weblogs and discussion forums
1. Information systems
  1. World Wide Web
    1. Web applications
      1. Social networks
    2. Web mining

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cover image ACM Conferences

WI '17: Proceedings of the International Conference on Web Intelligence

August 2017

1284 pages

ISBN:9781450349512

DOI:10.1145/3106426

Conference Chair:
Amit Sheth
Wright State University GuoROLE@GENERAL CHAIR
,
General Chairs:
Axel Ngonga
Leipzig University, Germany
,
yin Wang
Chongqing University of Posts and Telecommunications, China
,
Elizabeth Chang
The University of New South Wales, Australia
,
Dominik Ślęzak
Infobright Inc. & University of Warsaw, Poland
,
Bogdan Franczyk
Leipzig University, Germany
,
Program Chairs:
Rainer Alt
Leipzig University, Germany
,
Xiaohui Tao
University of Southern Queensland, Australia

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGAI: ACM Special Interest Group on Artificial Intelligence
TCII: IEEE Computer Society Technical Committee on Intelligent Informatics
Web Intelligence Consortium

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 August 2017

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Elsevier
Science Foundation of Ireland

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WI '17

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SIGAI
TCII

WI '17: International Conference on Web Intelligence 2017

August 23 - 26, 2017

Leipzig, Germany

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WI '17 Paper Acceptance Rate 118 of 178 submissions, 66%;

Overall Acceptance Rate 118 of 178 submissions, 66%

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Cited By

Timilsina MFigueroa A(2023)Neural age screening on question answering communitiesEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.106219123(106219)Online publication date: Aug-2023
https://doi.org/10.1016/j.engappai.2023.106219
Figueroa ATimilsina M(2021)What identifies different age cohorts in Yahoo! Answers?Knowledge-Based Systems10.1016/j.knosys.2021.107278(107278)Online publication date: Jul-2021
https://doi.org/10.1016/j.knosys.2021.107278
Akella AAlhoori HKondamudi PFreeman CZhou H(2021)Early indicators of scientific impact: Predicting citations with altmetricsJournal of Informetrics10.1016/j.joi.2020.10112815:2(101128)Online publication date: May-2021
https://doi.org/10.1016/j.joi.2020.101128
Timilsina Md’Aquin MYang H(2019)Heat diffusion approach for scientific impact analysis in social mediaSocial Network Analysis and Mining10.1007/s13278-019-0560-39:1Online publication date: 25-Apr-2019
https://doi.org/10.1007/s13278-019-0560-3
Timilsina MYang HRebholz-Schuhmann D(2018)A 2-Layered Graph Based Diffusion Approach for Altmetric Analysis2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)10.1109/ASONAM.2018.8508290(463-466)Online publication date: Aug-2018
https://doi.org/10.1109/ASONAM.2018.8508290

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