loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Nicola Assolini 1 ; Adelaide Baronchelli 2 ; Matteo Cristani 1 ; Luca Pasetto 1 ; Francesco Olivieri 3 ; Roberto Ricciuti 2 and Claudio Tomazzoli 4

Affiliations: 1 Department of Computer Science, University of Verona, Italy ; 2 Department of Economics, University of Verona, Italy ; 3 IIIS, Griffith University, Australia ; 4 CITERA Interdepartmental Centre, Sapienza University of Rome, Italy

Keyword(s): Text Analytics, Web Analytics, Web Repository, Economic Analysis.

Abstract: There is a growing attention, in the research communities of political economics, onto the potential of text analytics in classifying documents with economic content. This interest extends the data analytics approach that has been the traditional base for economic theory with scientific perspective. To devise a general method for prediction applicability, we identify some phases of a methodology and perform tests on a large well-structured repository of resource contracts containing documents related to resources. The majority of these contracts involve mining resources. In this paper we prove that, by the usage of text analytics measures, we can cluster these documents on three indicators: fairness of the contract content, transparency of the document themselves, and applicability of the clauses of the contract intended to guarantee execution on an international basis. We achieve these results, consistent with a gold-standard test obtained with human experts, using text similarity b ased on the basic notions of bag of words, the index tf-idf, and three distinct cut-off measures. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.238.130.41

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Assolini, N.; Baronchelli, A.; Cristani, M.; Pasetto, L.; Olivieri, F.; Ricciuti, R. and Tomazzoli, C. (2021). Text Analytics Can Predict Contract Fairness, Transparency and Applicability. In Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-536-4; ISSN 2184-3252, SciTePress, pages 316-323. DOI: 10.5220/0010660700003058

@conference{webist21,
author={Nicola Assolini. and Adelaide Baronchelli. and Matteo Cristani. and Luca Pasetto. and Francesco Olivieri. and Roberto Ricciuti. and Claudio Tomazzoli.},
title={Text Analytics Can Predict Contract Fairness, Transparency and Applicability},
booktitle={Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST},
year={2021},
pages={316-323},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010660700003058},
isbn={978-989-758-536-4},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST
TI - Text Analytics Can Predict Contract Fairness, Transparency and Applicability
SN - 978-989-758-536-4
IS - 2184-3252
AU - Assolini, N.
AU - Baronchelli, A.
AU - Cristani, M.
AU - Pasetto, L.
AU - Olivieri, F.
AU - Ricciuti, R.
AU - Tomazzoli, C.
PY - 2021
SP - 316
EP - 323
DO - 10.5220/0010660700003058
PB - SciTePress