eprintid: 10194783
rev_number: 10
eprint_status: archive
userid: 699
dir: disk0/10/19/47/83
datestamp: 2024-07-19 10:49:47
lastmod: 2024-07-19 10:49:47
status_changed: 2024-07-19 10:49:47
type: proceedings_section
metadata_visibility: show
sword_depositor: 699
creators_name: Mitic, Peter
title: Is Positive Sentiment Missing in Corporate Reputation?
ispublished: pub
divisions: UCL
divisions: B04
divisions: F48
keywords: State-Space, Kalman filter, Kalman, Forward Filtering Backward Sampling, FFBS, MCMC, TNA, reputation, sentiment, missing sentiment, missing positive sentiment, negative bias
note: © The Author 2024. Original content in this paper is licensed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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.
date: 2024
date_type: published
publisher: SCITEPRESS - Science and Technology Publications
official_url: http://dx.doi.org/10.5220/0012763100003756
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 2298060
doi: 10.5220/0012763100003756
isbn_13: 978-989-758-707-8
lyricists_name: Mitic, Peter
lyricists_id: PMITI76
actors_name: Mitic, Peter
actors_id: PMITI76
actors_role: owner
full_text_status: public
pres_type: paper
publication: Proceedings of the 13th International Conference on Data Science, Technology and Applications
volume: 1
pagerange: 71-81
event_title: 13th International Conference on Data Science, Technology and Applications
event_location: Dijon, France
event_dates: 9th-11th July 2024
issn: 2184-285X
book_title: Proceedings of the 13th International Conference on Data Science, Technology and Applications
citation:        Mitic, Peter;      (2024)    Is Positive Sentiment Missing in Corporate Reputation?                     In:  Proceedings of the 13th International Conference on Data Science, Technology and Applications.  (pp. pp. 71-81).  SCITEPRESS - Science and Technology Publications       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10194783/1/Paper54_MissingSentiment_DATA2024_V2.pdf