Is Positive Sentiment Missing in Corporate Reputation?

Peter Mitic

2024

Abstract

The value of a perceived negative bias is quantified in the context of corporate reputation time series, derived by exhaustive data mining and automated natural language processing. Two methods of analysis are proposed: State-Space using a Kalman filter time series with a Normal distribution profile, and Forward Filtering Backward Sampling for those without. Normality tests indicate that approximately 92% of corporate reputation time series do fit the Normal profile. The results indicate that observed positive reputation profiles should be boosted by approximately 4% to account for negative bias. Examination of the observed balance between negative and positive sentiment in reputation time series indicates dependence on the sentiment calculation method, and region. Positive sentiment predominates in the US, Japan and parts of Western Europe, but not in the UK or in Hong Kong/China.

Paper Citation

in Harvard Style

Mitic P. (2024). Is Positive Sentiment Missing in Corporate Reputation?. In Proceedings of the 13th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-707-8, SciTePress, pages 71-81. DOI: 10.5220/0012763100003756

in Bibtex Style

@conference{data24,
author={Peter Mitic},
title={Is Positive Sentiment Missing in Corporate Reputation?},
booktitle={Proceedings of the 13th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2024},
pages={71-81},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012763100003756},
isbn={978-989-758-707-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Is Positive Sentiment Missing in Corporate Reputation?
SN - 978-989-758-707-8
AU - Mitic P.
PY - 2024
SP - 71
EP - 81
DO - 10.5220/0012763100003756
PB - SciTePress