research-article

ELEVATE: A Framework for Entity-level Event Diffusion Prediction into Foreign Language Communities

Authors:

Marc SpaniolAuthors Info & Claims

WebSci '17: Proceedings of the 2017 ACM on Web Science Conference

Pages 111 - 120

https://doi.org/10.1145/3091478.3091481

Published: 25 June 2017 Publication History

Abstract

The accessibility to news via the Web or other "traditional" media allows a rapid diffusion of information into almost every part of the world. These reports cover the full spectrum of events, ranging from locally relevant ones up to those that gain global attention. The societal impact of an event can be relatively easily "measured" by the attention it attracts (e.g. in the number of responses it receives and/or provokes) in the news or social media. However, this does not necessarily reflect its inter-cultural impact and its diffusion into other communities. In order to address the issue of predicting the spread of information into foreign language communities we introduce the ELEVATE framework. ELEVATE exploits entity information from Web contents and harnesses location related data for language-related event diffusion prediction. Our experiments on event spreading across Wikipedia communities of different language demonstrate the viability of our approach and improvement over state-of-the-art approaches.

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Cited By

Kumar A(2020)Towards a Better Contextualization of Web Contents via Entity-Level AnalyticsAdvances in Information Retrieval10.1007/978-3-030-45442-5_80(613-618)Online publication date: 8-Apr-2020
https://doi.org/10.1007/978-3-030-45442-5_80
Govind Alec CSpaniol M(2018)ELEVATE-Live: Assessment and Visualization of Online News Virality via Entity-Level AnalyticsWeb Engineering10.1007/978-3-319-91662-0_40(482-486)Online publication date: 20-May-2018
https://doi.org/10.1007/978-3-319-91662-0_40
Gottschalk SBernacchi VRogers RDemidova E(2018)Towards Better Understanding Researcher Strategies in Cross-Lingual Event AnalyticsDigital Libraries for Open Knowledge10.1007/978-3-030-00066-0_12(139-151)Online publication date: 5-Sep-2018
https://doi.org/10.1007/978-3-030-00066-0_12

Index Terms

ELEVATE: A Framework for Entity-level Event Diffusion Prediction into Foreign Language Communities
1. Information systems
  1. World Wide Web
    1. Web applications
    2. Web mining

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cover image ACM Conferences

WebSci '17: Proceedings of the 2017 ACM on Web Science Conference

June 2017

438 pages

ISBN:9781450348966

DOI:10.1145/3091478

Conference Chairs:
Peter Fox
Rensselaer Polytechnic Institute, USA
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Deborah McGuinness
Rensselaer Polytechnic Institute, USA
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Lindsay Poirer
Rensselaer Polytechnic Institute, USA
,
Program Chairs:
Paolo Boldi
Universita degli Studi di Milano, Italy
,
Katharina Kinder-Kurlanda
GESIS - Leibniz Institute for the Social Sciences, Germany

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Published: 25 June 2017

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WebSci '17: ACM Web Science Conference

June 25 - 28, 2017

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WebSci '17 Paper Acceptance Rate 30 of 85 submissions, 35%;

Overall Acceptance Rate 245 of 933 submissions, 26%

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Cited By

Kumar A(2020)Towards a Better Contextualization of Web Contents via Entity-Level AnalyticsAdvances in Information Retrieval10.1007/978-3-030-45442-5_80(613-618)Online publication date: 8-Apr-2020
https://doi.org/10.1007/978-3-030-45442-5_80
Govind Alec CSpaniol M(2018)ELEVATE-Live: Assessment and Visualization of Online News Virality via Entity-Level AnalyticsWeb Engineering10.1007/978-3-319-91662-0_40(482-486)Online publication date: 20-May-2018
https://doi.org/10.1007/978-3-319-91662-0_40
Gottschalk SBernacchi VRogers RDemidova E(2018)Towards Better Understanding Researcher Strategies in Cross-Lingual Event AnalyticsDigital Libraries for Open Knowledge10.1007/978-3-030-00066-0_12(139-151)Online publication date: 5-Sep-2018
https://doi.org/10.1007/978-3-030-00066-0_12

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