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Various means exist for obtaining information about a company. However, many of them are not timely and, from the investor’ s point of view, do not have enough information. In particular, it is even more difficult to find out trends of diversified companies with multiple segments. Therefore, this study aims to extract timely information on the trends of each segment of a company from news data using BERTopic. The analysis targets news headlines of diversified electronics firms listed on the Japanese stock market. The sample period was 24 years, from 1996 to 2019, and the number of news items for analysis was 26,058. As a result of the analysis, we found that (1) BERTopic can classify the target news into 46 topics, (2) it is possible to identify company segments and extract trends in company activities from the classified topics, and (3) it is also possible to visualize the time-series transition of topics related to each segment. (4) The results obtained from the analysis were used to determine the value of the company's investment in the market. In addition, the results obtained from the analysis were consistent with the descriptions in the annual reports. These results indicate the possibility of obtaining highly immediate information on corporate trends, such as R&D, through the analysis of news headlines via BERTopic.
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Stored only when both papers are in the corpus — 10 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.