@inproceedings{papanikolaou-papageorgiou-2020-protest,
title = "Protest Event Analysis: A Longitudinal Analysis for {G}reece",
author = "Papanikolaou, Konstantina and
Papageorgiou, Haris",
editor = {H{\"u}rriyeto{\u{g}}lu, Ali and
Y{\"o}r{\"u}k, Erdem and
Zavarella, Vanni and
Tanev, Hristo},
booktitle = "Proceedings of the Workshop on Automated Extraction of Socio-political Events from News 2020",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/2020.aespen-1.10",
pages = "57--62",
abstract = "The advent of Big Data has shifted social science research towards computational methods. The volume of data that is nowadays available has brought a radical change in traditional approaches due to the cost and effort needed for processing. Knowledge extraction from heterogeneous and ample data is not an easy task to tackle. Thus, interdisciplinary approaches are necessary, combining experts of both social and computer science. This paper aims to present a work in the context of protest analysis, which falls into the scope of Computational Social Science. More specifically, the contribution of this work is to describe a Computational Social Science methodology for Event Analysis. The presented methodology is generic in the sense that it can be applied in every event typology and moreover, it is innovative and suitable for interdisciplinary tasks as it incorporates the human-in-the-loop. Additionally, a case study is presented concerning Protest Analysis in Greece over the last two decades. The conceptual foundation lies mainly upon claims analysis, and newspaper data were used in order to map, document and discuss protests in Greece in a longitudinal perspective.",
language = "English",
ISBN = "979-10-95546-50-4",
}
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<abstract>The advent of Big Data has shifted social science research towards computational methods. The volume of data that is nowadays available has brought a radical change in traditional approaches due to the cost and effort needed for processing. Knowledge extraction from heterogeneous and ample data is not an easy task to tackle. Thus, interdisciplinary approaches are necessary, combining experts of both social and computer science. This paper aims to present a work in the context of protest analysis, which falls into the scope of Computational Social Science. More specifically, the contribution of this work is to describe a Computational Social Science methodology for Event Analysis. The presented methodology is generic in the sense that it can be applied in every event typology and moreover, it is innovative and suitable for interdisciplinary tasks as it incorporates the human-in-the-loop. Additionally, a case study is presented concerning Protest Analysis in Greece over the last two decades. The conceptual foundation lies mainly upon claims analysis, and newspaper data were used in order to map, document and discuss protests in Greece in a longitudinal perspective.</abstract>
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%0 Conference Proceedings
%T Protest Event Analysis: A Longitudinal Analysis for Greece
%A Papanikolaou, Konstantina
%A Papageorgiou, Haris
%Y Hürriyetoğlu, Ali
%Y Yörük, Erdem
%Y Zavarella, Vanni
%Y Tanev, Hristo
%S Proceedings of the Workshop on Automated Extraction of Socio-political Events from News 2020
%D 2020
%8 May
%I European Language Resources Association (ELRA)
%C Marseille, France
%@ 979-10-95546-50-4
%G English
%F papanikolaou-papageorgiou-2020-protest
%X The advent of Big Data has shifted social science research towards computational methods. The volume of data that is nowadays available has brought a radical change in traditional approaches due to the cost and effort needed for processing. Knowledge extraction from heterogeneous and ample data is not an easy task to tackle. Thus, interdisciplinary approaches are necessary, combining experts of both social and computer science. This paper aims to present a work in the context of protest analysis, which falls into the scope of Computational Social Science. More specifically, the contribution of this work is to describe a Computational Social Science methodology for Event Analysis. The presented methodology is generic in the sense that it can be applied in every event typology and moreover, it is innovative and suitable for interdisciplinary tasks as it incorporates the human-in-the-loop. Additionally, a case study is presented concerning Protest Analysis in Greece over the last two decades. The conceptual foundation lies mainly upon claims analysis, and newspaper data were used in order to map, document and discuss protests in Greece in a longitudinal perspective.
%U https://aclanthology.org/2020.aespen-1.10
%P 57-62
Markdown (Informal)
[Protest Event Analysis: A Longitudinal Analysis for Greece](https://aclanthology.org/2020.aespen-1.10) (Papanikolaou & Papageorgiou, AESPEN 2020)
ACL
- Konstantina Papanikolaou and Haris Papageorgiou. 2020. Protest Event Analysis: A Longitudinal Analysis for Greece. In Proceedings of the Workshop on Automated Extraction of Socio-political Events from News 2020, pages 57–62, Marseille, France. European Language Resources Association (ELRA).