What is it about?

The paper uses text mining and semantic algorithms to tag innovative firms and offer an alternative perspective to classify industrial activities. Instead of referring to firms’ standard industrial classification codes, we gather information from companies’ websites and corpo- rate purposes, extract keywords and generate tags concerning firms’ activities, specializations, and competences

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Why is it important?

Evidence is interesting because allows us to understand ‘what firms do’ in a more penetrating and updated way than referring to standard industrial classifi- cation codes. Moreover, through matching firms’ keywords, we can explore the degree of closeness between the firms under observation, a measure by which researchers can derive industrial proximity


The analysis can provide policymakers with a detailed and comprehen- sive picture of the innovative trajectories underlying the industrial structure in a geographic area

Alessandro Marra
Universita degli Studi Gabriele d'Annunzio Chieti e Pescara

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This page is a summary of: Using text data instead of SIC codes to tag innovative firms and classify industrial activities, PLoS ONE, June 2022, PLOS,
DOI: 10.1371/journal.pone.0270041.
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