| Title | Text Analytics and Big Data in the Financial domain |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Kuilboer, Jean-Pierre, Stull, Tristan |
| Conference Name | 2021 16th Iberian Conference on Information Systems and Technologies (CISTI) |
| Keywords | Adaptation models, Analytical models, analytics, Big Data, CFPB, composability, consumer complaint narratives, Data models, Decision Support System, Human Behavior, Metrics, natural language processing, Pipelines, pubcrawl, Scalability, text analytics, text mining, topic modeling |
| Abstract | This research attempts to provide some insights on the application of text mining and Natural Language Processing (NLP). The application domain is consumer complaints about financial institutions in the USA. As an advanced analytics discipline embedded within the Big Data paradigm, the practice of text analytics contains elements of emergent knowledge processes. Since our experiment should be able to scale up we make use of a pipeline based on Spark-NLP. The usage scenario is adapting the model to a specific industrial context and using the dataset offered by the "Consumer Financial Protection Bureau" to illustrate the application. |
| DOI | 10.23919/CISTI52073.2021.9476434 |
| Citation Key | kuilboer_text_2021 |
Text Analytics and Big Data in the Financial domain