title: Using Internet search engines to estimate word frequency
abstract: The present research investigated Internet search engines as a rapid, cost-effective alternative for estimating word frequencies. Frequency estimates for 382 words were obtained and compared across four methods: (1) Internet search engines, (2) the Kucera and Francis (1967) analysis of a traditional linguistic corpus, (3) the CELEX English linguistic database (Baayen et al., 1995), and (4) participant ratings of familiarity. The results showed that Internet search engines produced frequency estimates that were highly consistent with those reported by Kucera and Francis and those calculated from CELEX, highly consistent across search engines, and very reliable over a 6 month period of time. Additional results suggested that Internet search engines are an excellent option when traditional word frequency analyses do not contain the necessary data (e.g., estimates for forenames and slang). In contrast, participants' familiarity judgments did not correspond well with the more objective estimates of word frequency. Researchers are advised to use search engines with large databases (e.g., AltaVista) to ensure the greatest representativeness of the frequency estimates
keyphrases: Internet search engines linguistic corpus CELEX English linguistic database large databases word frequency estimation participant familiarity ratings