Diachronic profile of startup companies through social media
Bibliographic Data
| ID | 4658193 |
|---|---|
| Authors | Ana Rita Peixoto (0000-0001-7618-5994, Iscte – Instituto Universitário de Lisboa, corresponding author), Ana De Almeida (0000-0001-9519-4634, Iscte – Instituto Universitário de Lisboa), Nuno António (0000-0002-4801-2487, Centro de Investigação em Artes e Comunicação), Fernando Batista (0000-0002-1075-0177, Iscte – Instituto Universitário de Lisboa), Ricardo Ribeiro (0000-0002-2058-693X, Iscte – Instituto Universitário de Lisboa) |
| Year | 2023 |
| Volume | 13 |
| Issue | 1 |
| Pages | 52-52 |
| Publication date | 2023-03-18 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-023-01055-2 |
| PMID | 36968256 |
| OpenAlex | W4327723648 |
| Language | EN |
| Citations received | 1 |
| References cited | 30 |
Social media platforms have become powerful tools for startups, helping them find customers and raise funding. In this study, we applied a social media intelligence-based methodology to analyze startups' content and to understand how their communication strategies may differ during their scaling process. To understand if a startup's social media content reflects its current business maturation position, we first defined an adequate life cycle model for startups based on funding rounds and product maturity. Using Twitter as the source of information and selecting a sample of known Portuguese IT startups at different phases of their life cycle, we analyzed their Twitter data. After preprocessing the data, using latent Dirichlet allocation, topic modeling techniques enabled the categorization of the data according to the topics arising in the published contents of the startups, making it possible to discover that contents can be grouped into five specific topics: "Fintech and ML," "IT," "Business Operations," "Product/Service R&D," and "Bank and Funding." By comparing those profiles against the startup's life cycle, we were able to understand how contents change over time. This provided a diachronic profile for each company, showing that while certain topics remain prevalent in the startup's scaling, others depend on a particular phase of the startup's cycle. Our analysis revealed that startups' social media content differs along their life cycle, highlighting the importance of understanding how startups use social media at different stages of their development
Business · Industrial organization · Social media · World Wide Web · Computer Science · Digital Marketing and Social Media · FinTech, Crowdfunding, Digital Finance · Technology Adoption and User Behaviour
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| Unique citing works | 1 |
|---|---|
| Citations per year | 0,33 |
| Citation span | 2023 - 2023 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |