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Este trabalho apresenta o desenvolvimento de uma ferramenta web projetada para identificar perfis de usuários em várias plataformas de redes sociais, como Twitter, Facebook e Instagram, empregando exclusivamente medidas de similaridade de texto. O estudo se concentra na utilização da distância de Levenshtein, uma métrica conhecida por medir a diferença entre sequências de caracteres, para avaliar a semelhança entre usernames e nomes de perfil, buscando determinar a eficácia dessa abordagem em produzir resultados precisos na identificação de perfis correspondentes entre diferentes plataformas. A pesquisa conduz uma análise do desempenho e da precisão dessa métrica, explorando e implementando estratégias para aprimorar esses aspectos. Além disso, descreve o processo de criação da ferramenta web, destacando como ela facilita a construção de um banco de dados que associa perfis digitais a indivíduos reais. A aplicação da distância de Levenshtein permite uma identificação mais eficiente e rápida de conexões entre perfis de diferentes redes sociais, potencializando o reconhecimento e a análise de presenças online de usuários em múltiplos ambientes digitais.

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This work presents the development of a web tool designed to identify user profiles on various social media platforms, such as Twitter, Facebook and Instagram, exclusively employing text similarity measures. The study focuses on using the Levenshtein distance, a metric known for measuring the difference between sequences of characters, to evaluate the similarity between usernames and profile names, seeking to determine the effectiveness of this approach in producing accurate results in identifying matching profiles between different platforms. The research conducts an analysis of the performance and accuracy of this metric, exploring and implementing strategies to improve these aspects. Furthermore, it describes the process of creating the web tool, highlighting how it facilitates the construction of a database that associates digital profiles with real individuals. The application of Levenshtein distance allows for a more efficient and rapid identification of connections between profiles from different social networks, enhancing the recognition and analysis of users' online presence in multiple digital environments.

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1	Mariana Barreto(marianabarreto@aluno.puc-rio.br)
2	Sérgio Lifschitz(sergio@inf.puc-rio.br)

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2	Li, Y., Peng, Y., Zhang, Z., Yin, H., and Xu, Q. (2018). Matching user accounts across social networks based on username and display name. World Wide Web, 22(3):1075–1097.
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5	Shu, K., Wang, S., Tang, J., Zafarani, R., and Liu, H. (2017). User identity linkage across online social networks: A review. Acm Sigkdd Explorations Newsletter, 18(2):5–17.
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8	Zhang, H., Kan, M.-Y., Liu, Y., and Ma, S. (2014). Online social network profile linkage. In Information Retrieval Technology: 10th Asia Information Retrieval Societies Con- ference, AIRS 2014, Kuching, Malaysia, December 3-5, 2014. Proceedings 10, pages 197–208. Springer.

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