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Identifying startups business opportunities from UGC on twitter chatting: an exploratory analysis

2021-09Journal article Open access
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dc.contributor.authorSaura, José Ramón
dc.contributor.authorReyes-Menéndez, Ana
dc.contributor.authordeMatos, Nelson
dc.contributor.authorCorreia, Marisol B.
dc.date.accessioned2021-10-07T19:53:34Z
dc.date.available2021-10-07T19:53:34Z
dc.date.issued2021-09
dc.description.abstractThe startup business ecosystem in India has experienced exponential growth. The amount of investment in Indian startups in the last decade demonstrates the strong interest of the technology industry to these business models based on innovation. In this context, the present study aims to identify investment opportunities for investors in Indian startups by identifying key indicators that characterize the startup ecosystem in India. To this end, a three steps data mining method is developed using data mining techniques. First, a sentiment analysis (SA), a machine learning approach that classifies the topics into groups expressing feelings, is applied to a dataset. Next, we develop a Latent Dirichlet Allocation (LDA) model, a topic-modeling technique that divides the sample of n = 14.531 tweets from Twitter into topics, using user-generated content (UGC) as data. Finally, in order to identify the characteristics of each topic we apply textual analysis (TA) to identify key indicators. The originality of the present study lies in the methodological process used for data analysis. Our results also contribute to the literature on startups. The results demonstrate that the Indian startup ecosystem is influenced by areas such as fintech, innovation, crowdfunding, hardware, funds, competition, artificial intelligence, augmented reality and electronic commerce. Of note, in view of the exploratory approach of the present study, the results and implications should be taken as descriptive, rather than determining for future investments in the Indian startup ecosystem.pt_PT
dc.description.sponsorshipUIDB/04470/2020, UIDB/04020/2020pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/jtaer16060108pt_PT
dc.identifier.issn0718-1876
dc.identifier.urihttp://hdl.handle.net/10400.1/17205
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationCentre for Tourism Research, Development and Innovation
dc.relationResearch Centre for Tourism, Sustainability and Well-being
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectStartups opportunitiespt_PT
dc.subjectUser-generated contentpt_PT
dc.subjectSentiment analysispt_PT
dc.subjectElectronic commercept_PT
dc.titleIdentifying startups business opportunities from UGC on twitter chatting: an exploratory analysispt_PT
dc.title.alternativeIdentificação de oportunidades de negócios de startups da UGC no twitter bate-papo: uma análise exploratóriapt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCentre for Tourism Research, Development and Innovation
oaire.awardTitleResearch Centre for Tourism, Sustainability and Well-being
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04470%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04020%2F2020/PT
oaire.citation.endPage1944pt_PT
oaire.citation.issue6pt_PT
oaire.citation.startPage1929pt_PT
oaire.citation.titleJournal of Theoretical and Applied Electronic Commerce Researchpt_PT
oaire.citation.volume16pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameCorreia
person.givenNameMarisol B.
person.identifier.ciencia-idFE15-819A-4535
person.identifier.orcid0000-0002-1788-6114
person.identifier.scopus-author-id55333058000
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication.latestForDiscoveryee01864e-dec4-4285-a4b7-4ccb53d9afaa
relation.isProjectOfPublication779ad4fe-bc72-4d16-a6a9-19de115e63a9
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