Cargando…

Studying social media sentiment using human validated analysis

The measurement of online sentiment is a developing field in social science and big data research. The methodology from this study provides an analysis of online sentiment using a unique combination of NLP and human validation techniques in order to create net sentiment scores and categorise topics...

Descripción completa

Detalles Bibliográficos
Autores principales: Lappeman, James, Clark, Robyn, Evans, Jordan, Sierra-Rubia, Lara, Gordon, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7152698/
https://www.ncbi.nlm.nih.gov/pubmed/32300546
http://dx.doi.org/10.1016/j.mex.2020.100867
_version_ 1783521534538678272
author Lappeman, James
Clark, Robyn
Evans, Jordan
Sierra-Rubia, Lara
Gordon, Patrick
author_facet Lappeman, James
Clark, Robyn
Evans, Jordan
Sierra-Rubia, Lara
Gordon, Patrick
author_sort Lappeman, James
collection PubMed
description The measurement of online sentiment is a developing field in social science and big data research. The methodology from this study provides an analysis of online sentiment using a unique combination of NLP and human validation techniques in order to create net sentiment scores and categorise topics of online conversation. The study focused on measuring the online sentiment of South Africa's major banks (covering almost the entire retail banking industry) over a 12-month period. Through this methodology, firms are able to track shifts in online sentiment (including extreme firestorms) as well as to monitor relevant conversation topics. To date, no published methodology combines the use of big data NLP and human validation in such a structured way. • Microsampling for manual validation of sentiment analysis (both qualitative and quantitative approaches in order to obtain the most accurate results); • Sentiment measurement; • Sentiment map.
format Online
Article
Text
id pubmed-7152698
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-71526982020-04-16 Studying social media sentiment using human validated analysis Lappeman, James Clark, Robyn Evans, Jordan Sierra-Rubia, Lara Gordon, Patrick MethodsX Social Science The measurement of online sentiment is a developing field in social science and big data research. The methodology from this study provides an analysis of online sentiment using a unique combination of NLP and human validation techniques in order to create net sentiment scores and categorise topics of online conversation. The study focused on measuring the online sentiment of South Africa's major banks (covering almost the entire retail banking industry) over a 12-month period. Through this methodology, firms are able to track shifts in online sentiment (including extreme firestorms) as well as to monitor relevant conversation topics. To date, no published methodology combines the use of big data NLP and human validation in such a structured way. • Microsampling for manual validation of sentiment analysis (both qualitative and quantitative approaches in order to obtain the most accurate results); • Sentiment measurement; • Sentiment map. Elsevier 2020-03-19 /pmc/articles/PMC7152698/ /pubmed/32300546 http://dx.doi.org/10.1016/j.mex.2020.100867 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Social Science
Lappeman, James
Clark, Robyn
Evans, Jordan
Sierra-Rubia, Lara
Gordon, Patrick
Studying social media sentiment using human validated analysis
title Studying social media sentiment using human validated analysis
title_full Studying social media sentiment using human validated analysis
title_fullStr Studying social media sentiment using human validated analysis
title_full_unstemmed Studying social media sentiment using human validated analysis
title_short Studying social media sentiment using human validated analysis
title_sort studying social media sentiment using human validated analysis
topic Social Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7152698/
https://www.ncbi.nlm.nih.gov/pubmed/32300546
http://dx.doi.org/10.1016/j.mex.2020.100867
work_keys_str_mv AT lappemanjames studyingsocialmediasentimentusinghumanvalidatedanalysis
AT clarkrobyn studyingsocialmediasentimentusinghumanvalidatedanalysis
AT evansjordan studyingsocialmediasentimentusinghumanvalidatedanalysis
AT sierrarubialara studyingsocialmediasentimentusinghumanvalidatedanalysis
AT gordonpatrick studyingsocialmediasentimentusinghumanvalidatedanalysis