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Transforming Online Review Analysis into Visual Insights: A Literature Review on Data Visualization for Online Reviews Analysis
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 1.36 MB | Adobe PDF |
Orientador(es)
Resumo(s)
Online Customer Reviews (OCRs) have become an indispensable source of information in the
context of eWOM, playing a decisive role in understanding consumer behavior and
formulating business strategies. However, the high volume, diversity, and complexity of these
data present significant challenges for their effective analysis and interpretation. In addition,
the absence of literature that systematically integrates the advanced techniques of data
visualization and sentiment analysis applied to OCRs represents an important gap in this
domain. This lack of integration limits the extraction of deep, actionable insights, which are
essential for researchers and practitioners looking to optimize customer experience
monitoring and strategic decision-making. The main objective of this study was to critically
analyze the data visualization techniques applied to the analysis of OCRs . To this end, a
systematic review of the literature was carried out in databases such as Scopus, ScienceDirect,
and IEEE, applying rigorous criteria for selection and qualitative analysis of the studies,
focusing on the analytical and visual techniques used. The results demonstrate that methods
that combine interactivity, semantic analysis, and temporal visualization, such as interactive
dashboards, co-occurrence networks, and thematic maps integrated with aspect-based
sentiment analysis, provide a deeper and more dynamic understanding of behavior patterns
and critical areas in OCRs. This integrated approach overcomes the limitations of previous
studies that treated visualization and Online Customer Reviews analysis separately. Although
there are limitations related to the scarcity of integrated studies and methodological diversity,
the work paves the way for the development of adaptive visual frameworks and for the realtime integration of sentiment analyses. With these contributions, this study offers a solid
foundation to advance research and improve practice in online review analysis, promoting a
strategic and innovative understanding of the consumer.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
Palavras-chave
Online customer reviews Data visualization Sentiment analysis Consumer behavior Interactive dashboards SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure SDG 12 - Responsible production and consumption SDG 17 - Partnerships for the goals