Intelligent Corporate Sustainability report scoring solution using machine learning approach to text categorization

Amir Mohammad Shahi; Biju Issac; Jashua Rajesh Modapothala

doi:10.1109/STUDENT.2012.6408409

Intelligent Corporate Sustainability report scoring solution using machine learning approach to text categorization

Amir Mohammad Shahi^*, Biju Issac, Jashua Rajesh Modapothala

^*Corresponding author for this work

Computer Information Sciences Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Citations (Scopus)

Abstract

Development of an intelligent software system to analyze and score Corporate Sustainability reports within the Global Reporting Initiative (GRI) framework has been well foreseen and in a high demand since the latest framework's publication in 2000's. As the number of reporting organizations and published reports is increasing exponentially, development of a software system to automate the daunting manual scoring process seems even more vital. We describe our preliminary efforts and the related results of our efforts in building such software through application of machine learning approach to text classification. Conduction of earlier training on thousands of sample documents to construct machine learning based classifiers inductively is our primary approach to solving this problem.

Original language	English
Title of host publication	2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012 - Conference Booklet
Publisher	IEEE
Pages	227-232
Number of pages	6
ISBN (Electronic)	9781467317054
ISBN (Print)	9781467316491
DOIs	https://doi.org/10.1109/STUDENT.2012.6408409
Publication status	Published - 11 Jan 2013
Event	3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012 - Kuala Lumpur, Malaysia Duration: 6 Oct 2012 → 9 Oct 2012

Conference

Conference	3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012
Country/Territory	Malaysia
City	Kuala Lumpur
Period	6/10/12 → 9/10/12

Keywords

corporate sustainability report
CSR
feature selection
Global reporting initiative
GRI
machine learning
NaiveBayes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/STUDENT.2012.6408409

Cite this

Shahi, A. M., Issac, B., & Modapothala, J. R. (2013). Intelligent Corporate Sustainability report scoring solution using machine learning approach to text categorization. In 2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012 - Conference Booklet (pp. 227-232). Article 6408409 IEEE. https://doi.org/10.1109/STUDENT.2012.6408409

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title = "Intelligent Corporate Sustainability report scoring solution using machine learning approach to text categorization",

abstract = "Development of an intelligent software system to analyze and score Corporate Sustainability reports within the Global Reporting Initiative (GRI) framework has been well foreseen and in a high demand since the latest framework's publication in 2000's. As the number of reporting organizations and published reports is increasing exponentially, development of a software system to automate the daunting manual scoring process seems even more vital. We describe our preliminary efforts and the related results of our efforts in building such software through application of machine learning approach to text classification. Conduction of earlier training on thousands of sample documents to construct machine learning based classifiers inductively is our primary approach to solving this problem.",

keywords = "corporate sustainability report, CSR, feature selection, Global reporting initiative, GRI, machine learning, NaiveBayes",

author = "Shahi, {Amir Mohammad} and Biju Issac and Modapothala, {Jashua Rajesh}",

year = "2013",

month = jan,

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doi = "10.1109/STUDENT.2012.6408409",

language = "English",

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pages = "227--232",

booktitle = "2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012 - Conference Booklet",

publisher = "IEEE",

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note = "3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012 ; Conference date: 06-10-2012 Through 09-10-2012",

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Shahi, AM, Issac, B & Modapothala, JR 2013, Intelligent Corporate Sustainability report scoring solution using machine learning approach to text categorization. in 2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012 - Conference Booklet., 6408409, IEEE, pp. 227-232, 3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012, Kuala Lumpur, Malaysia, 6/10/12. https://doi.org/10.1109/STUDENT.2012.6408409

Intelligent Corporate Sustainability report scoring solution using machine learning approach to text categorization. / Shahi, Amir Mohammad; Issac, Biju; Modapothala, Jashua Rajesh.
2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012 - Conference Booklet. IEEE, 2013. p. 227-232 6408409.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Shahi, Amir Mohammad

AU - Issac, Biju

AU - Modapothala, Jashua Rajesh

PY - 2013/1/11

Y1 - 2013/1/11

N2 - Development of an intelligent software system to analyze and score Corporate Sustainability reports within the Global Reporting Initiative (GRI) framework has been well foreseen and in a high demand since the latest framework's publication in 2000's. As the number of reporting organizations and published reports is increasing exponentially, development of a software system to automate the daunting manual scoring process seems even more vital. We describe our preliminary efforts and the related results of our efforts in building such software through application of machine learning approach to text classification. Conduction of earlier training on thousands of sample documents to construct machine learning based classifiers inductively is our primary approach to solving this problem.

AB - Development of an intelligent software system to analyze and score Corporate Sustainability reports within the Global Reporting Initiative (GRI) framework has been well foreseen and in a high demand since the latest framework's publication in 2000's. As the number of reporting organizations and published reports is increasing exponentially, development of a software system to automate the daunting manual scoring process seems even more vital. We describe our preliminary efforts and the related results of our efforts in building such software through application of machine learning approach to text classification. Conduction of earlier training on thousands of sample documents to construct machine learning based classifiers inductively is our primary approach to solving this problem.

KW - corporate sustainability report

KW - CSR

KW - feature selection

KW - Global reporting initiative

KW - GRI

KW - machine learning

KW - NaiveBayes

U2 - 10.1109/STUDENT.2012.6408409

DO - 10.1109/STUDENT.2012.6408409

M3 - Conference contribution

AN - SCOPUS:84873980967

SN - 9781467316491

SP - 227

EP - 232

BT - 2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012 - Conference Booklet

PB - IEEE

T2 - 3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012

Y2 - 6 October 2012 through 9 October 2012

ER -

Intelligent Corporate Sustainability report scoring solution using machine learning approach to text categorization

Abstract

Conference

Keywords

UN SDGs

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Cite this