Boosting Word Frequencies in Authorship Attribution

:speech_balloon: Speaker: Maciej Eder

:classical_building: Affiliation: Institute of Polish Language, Polish Academy of Sciences,
al. Mickiewicza 31, 31–120 Kraków, Poland

Title: Boosting Word Frequencies in Authorship Attribution

Abstract: In this paper, I introduce a simple method of computing relative word frequencies for authorship attribution and similar stylometric tasks. Rather than computing relative frequencies as the number of occurrences of a given word divided by the total number of tokens in a text, I argue that a more efficient normalization factor is the total number of relevant tokens only. The notion of relevant words includes synonyms and, usually, a few dozen other words in some ways semantically similar to a word in question. To determine such a semantic background, one of word embedding models can be used. The proposed method outperforms classical most-frequent-word approaches substantially, usually by a few percentage points depending on the input settings.

:newspaper: Link to paper