Using Web Text Analytics to Categorize the Business Focus of Innovative Digital Health Companies
Categorizing the market focus of larger samples of companies can be a tedious and time-consuming process for both researchers and business analysts interested in developing insights about emerging business sectors. The objective of this article is to suggest a text analytics approach to categorizing...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Carleton University
2021-10-01
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| Series: | Technology Innovation Management Review |
| Subjects: | |
| Online Access: | https://timreview.ca/timreview.ca/article/1457 |
| _version_ | 1818732107997904896 |
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| author | Abdulla Aweisi Daman Arora Renée Emby Madiha Rehman George Tanev Stoyan Tanev |
| author_facet | Abdulla Aweisi Daman Arora Renée Emby Madiha Rehman George Tanev Stoyan Tanev |
| author_sort | Abdulla Aweisi |
| collection | DOAJ |
| description | Categorizing the market focus of larger samples of companies can be a tedious and time-consuming process for both researchers and business analysts interested in developing insights about emerging business sectors. The objective of this article is to suggest a text analytics approach to categorizing the application areas of companies operating in the digital health sector based on the information provided on their websites. More specifically, we apply topic modeling on a collection of text documents, including information collected from the websites of a sample of 100 innovative digital health companies. The topic model helps in grouping the companies offering similar types of market offers. It enables identifying the companies that are most highly associated with each of the topics. In addition, it allows identifying some of the emerging themes that are discussed online by the companies, as well as their specific market offers. The results will be of interest to inspiring technology entrepreneurs, organizations supporting new ventures, and business accelerators interested to enhance their services to new venture clients. The development, operationalization, and automation of the company categorization process based on publicly available information is a methodological contribution that opens the opportunity for future applications in research and business practice. |
| first_indexed | 2024-12-17T23:28:19Z |
| format | Article |
| id | doaj.art-06ae0fb797604d55a2e615e738a65465 |
| institution | Directory Open Access Journal |
| issn | 1927-0321 |
| language | English |
| last_indexed | 2024-12-17T23:28:19Z |
| publishDate | 2021-10-01 |
| publisher | Carleton University |
| record_format | Article |
| series | Technology Innovation Management Review |
| spelling | doaj.art-06ae0fb797604d55a2e615e738a654652022-12-21T21:28:42ZengCarleton UniversityTechnology Innovation Management Review1927-03212021-10-01117/86578http://doi.org/10.22215/timreview/1457Using Web Text Analytics to Categorize the Business Focus of Innovative Digital Health CompaniesAbdulla AweisiDaman AroraRenée EmbyMadiha RehmanGeorge TanevStoyan Tanev0 Carleton University Categorizing the market focus of larger samples of companies can be a tedious and time-consuming process for both researchers and business analysts interested in developing insights about emerging business sectors. The objective of this article is to suggest a text analytics approach to categorizing the application areas of companies operating in the digital health sector based on the information provided on their websites. More specifically, we apply topic modeling on a collection of text documents, including information collected from the websites of a sample of 100 innovative digital health companies. The topic model helps in grouping the companies offering similar types of market offers. It enables identifying the companies that are most highly associated with each of the topics. In addition, it allows identifying some of the emerging themes that are discussed online by the companies, as well as their specific market offers. The results will be of interest to inspiring technology entrepreneurs, organizations supporting new ventures, and business accelerators interested to enhance their services to new venture clients. The development, operationalization, and automation of the company categorization process based on publicly available information is a methodological contribution that opens the opportunity for future applications in research and business practice.https://timreview.ca/timreview.ca/article/1457digital health sectormachine learningmarket offertopic modeling algorithmvalue propositionweb analytics |
| spellingShingle | Abdulla Aweisi Daman Arora Renée Emby Madiha Rehman George Tanev Stoyan Tanev Using Web Text Analytics to Categorize the Business Focus of Innovative Digital Health Companies Technology Innovation Management Review digital health sector machine learning market offer topic modeling algorithm value proposition web analytics |
| title | Using Web Text Analytics to Categorize the Business Focus of Innovative Digital Health Companies |
| title_full | Using Web Text Analytics to Categorize the Business Focus of Innovative Digital Health Companies |
| title_fullStr | Using Web Text Analytics to Categorize the Business Focus of Innovative Digital Health Companies |
| title_full_unstemmed | Using Web Text Analytics to Categorize the Business Focus of Innovative Digital Health Companies |
| title_short | Using Web Text Analytics to Categorize the Business Focus of Innovative Digital Health Companies |
| title_sort | using web text analytics to categorize the business focus of innovative digital health companies |
| topic | digital health sector machine learning market offer topic modeling algorithm value proposition web analytics |
| url | https://timreview.ca/timreview.ca/article/1457 |
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