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