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Home | Events Archive | Extracting Inter-Firm Alliance Networks via Text Mining

Extracting Inter-Firm Alliance Networks via Text Mining

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  • Date and time

    January 14, 2021
    14:00 - 15:00

If you are interested in joining the seminar, please send an email to Daniel Haerle or Sacha den Nijs.


I propose a text mining model for automatically extracting alliances between firms from news articles. I leverage the pre-trained language model RoBERTa (Liu et al., 2019) and a large amount of labeled examples from the SDC alliance database to fine-tune the model. The resulting system is able to detect alliance announcements in documents, extract the participating firms, and flag alliances according to their purpose. I show that the model is highly accurate in the firm name recognition and relation classification tasks. I run inference on a large corpus of news articles and show that the model can be used to significantly extend existing data sources.