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Handwriting analysis on the diaries of Rosamond Jacob

Sawant, Sharmistha S., Thakare, Saloni D., Greene, Derek orcid logoORCID: 0000-0001-8065-5418, Meaney, Gerardine orcid logoORCID: 0000-0002-5412-5007 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2023) Handwriting analysis on the diaries of Rosamond Jacob. In: 20th International Conference on Content-based Multimedia Indexing, 20-22 Sept 2023, Orleans, France. ISBN 979-8-4007-0912-8

Abstract
Handwriting is an art form that most people learn at an early age. Each person's writing style is unique with small changes as we grow older and as our mood changes. Here we analyse handwritten text in a culturally significant personal diary. We compare changes in handwriting and relate this to the sentiment of the written material and to the topic of diary entries. We identify handwritten text from digitised images and generate a canonical form for words using shape matching to compare how the same handwritten word appears over a period of time. For determining the sentiment of diary entries, we use the Hedonometer, a dictionary-based approach to scoring sentiment. We apply these techniques to the historical diary entries of Rosamond Jacob (1888-1960), an Irish writer and political activist whose daily diary entries report on the major events in Ireland during the first half of the last century.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Journaling; computer vision; shape matching; structural similarity index; sentiment analysis
Subjects:Computer Science > Image processing
Social Sciences > Political science
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > INSIGHT Centre for Data Analytics
Published in: Proceedings of the 20th International Conference on Content-based Multimedia Indexing (CBMI ’23). . Association for Computing Machinery (ACM). ISBN 979-8-4007-0912-8
Publisher:Association for Computing Machinery (ACM)
Official URL:https://doi.org/10.1145/3617233.3617255
Copyright Information:© 2023 Association for Computing Machinery
Funders:Science Foundation Ireland [12/RC/2289_P2]
ID Code:28915
Deposited On:18 Sep 2023 09:41 by Alan Smeaton . Last Modified 26 Jan 2024 15:07
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