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Home | Events Archive | Extracting firm alliance networks via text mining
Master's Thesis defense

Extracting firm alliance networks via text mining

  • Speaker
    Jacob Rauch
  • Location
  • Date and time

    September 28, 2020
    16:00 - 17:00

Abstract: We propose a text mining model for automatically extracting alliances between firms from news articles. We leverage the pre-trained language model RoBERTa (Liu et al., 2019) and a large amount of labeled examples from the SDC alliance data 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. We show that our model is highly accurate in the firm name recognition and relation classification tasks. We run inference on a large corpus of news articles and show that the model can add valuable data to existing sources.