Investigating the User Experience in the Process of Text Mining in Online Social Networks
| Autor: | Marcus Vinicius Carvalho Guelpeli, Jésyka M. A. Gonçalves, Caroline Q. Santos, Maria Lúcia Bento Villela |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Social Computing and Social Media: Experience Design and Social Network Analysis ISBN: 9783030776251 HCI (13) |
| DOI: | 10.1007/978-3-030-77626-8_18 |
| Popis: | With the advancement of technologies and the spread of the internet, online social networks have become increasingly popular. Associated with this growth, the volume of digital data made available by these media has significantly increased. In this context, there is an interest on the part of researchers to increasingly use online social networks as a source of data to obtain knowledge and develop important research in all scientific areas. Thus, this work aimed to investigate, through an exploratory and qualitative study, the difficulties and needs of researchers related to the data collection and the other steps of the text mining process in online social networks. The Underlying Discourse Unveiling Method was used to collect and analyze the data. The results show that users are dissatisfied with the existing tools that support them in this process. In addition, the results also highlight the needs of data researchers in order to create a tool that provides them a better user experience during text mining on online social networks (OSN), making this process more effective. |
| Databáze: | OpenAIRE |
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