{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T16:00:29Z","timestamp":1787673629359,"version":"build-2736575974"},"reference-count":17,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T00:00:00Z","timestamp":1744156800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Artif. Intell."],"abstract":"<jats:p>In this research note, we explore the integration of natural language processing (NLP) and web scraping techniques to develop a custom price index for measuring inflation. Using the Harmonized Index of Consumer Prices (HICP) as a benchmark, we created a database of consumer electronics product data through web scraping. Using the BERT model for classification, we achieved a high-performance classification of approximately 10,000 items into COICOP categories, with an accuracy of 94.56 %, macro precision of 79.41 %, and weighted precision of 94.07 % on validation data. Our custom index, particularly with weighted and median methodologies, demonstrated closer alignment with the official HICP while capturing more detailed price fluctuations within the market. Monthly inflation trends revealed variability that reflects price changes in the COICOP 091 category, contrasting with the relative stability of the official HICP. This work provides an alternative perspective on inflation measurement, highlighting the potential of computational approaches to enhance economic analysis.<\/jats:p>","DOI":"10.3389\/frai.2025.1520659","type":"journal-article","created":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T05:21:05Z","timestamp":1744176065000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["NLP-enhanced inflation measurement using BERT and web scraping"],"prefix":"10.3389","volume":"8","author":[{"given":"Martin","family":"Berki","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vanesa","family":"Andicsova","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Milos","family":"Oravec","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,4,9]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.2740600","article-title":"Forecasting inflation with online prices","author":"Aparicio","year":"2017","journal-title":"eBusiness and eCommerce J"},{"key":"B2","doi-asserted-by":"crossref","DOI":"10.3386\/w30613","article-title":"\u201cUnderstanding U.S. inflation during the covid era,\u201d","volume-title":"Working Paper 30613, National Bureau of Economic Research","author":"Ball","year":"2022"},{"key":"B3","doi-asserted-by":"publisher","first-page":"95","DOI":"10.3390\/economies10040095","article-title":"Computation of high-frequency sub-national spatial consumer price indexes using web scraping techniques","volume":"10","author":"Benedetti","year":"2022","journal-title":"Economies"},{"key":"B4","doi-asserted-by":"publisher","first-page":"117","DOI":"10.3386\/w4505","article-title":"The consumer price index as a measure of inflation","volume":"27","author":"Bryan","year":"1993","journal-title":"Monet. Econ"},{"key":"B5","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1177\/03015742241226517","article-title":"A comparative analysis of dslr and mirrorless cameras for dental photography","volume":"58","author":"Chitra","year":"2024","journal-title":"J. Indian Orthodontic Soc"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1912.09582","article-title":"Bertje: a dutch bert model","author":"de Vries","year":"2019","journal-title":"arXiv"},{"key":"B7","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","author":"Devlin","year":"2019"},{"key":"B8","doi-asserted-by":"crossref","DOI":"10.7208\/chicago\/9780226148571.001.0001","volume-title":"Price Index Concepts and Measurement","author":"Diewert","year":"2009"},{"key":"B9","doi-asserted-by":"crossref","first-page":"6040","DOI":"10.1109\/BigData47090.2019.9005594","article-title":"\u201cWeb scraping: State-of-the-art and areas of application,\u201d","volume-title":"2019 IEEE International Conference on Big Data (Big Data)","author":"Diouf","year":"2019"},{"key":"B10","volume-title":"Harmonized Index of Consumer Prices (HICP): Methodology and Practices","year":"2018"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1903.10318","article-title":"Fine-tune BERT for extractive summarization","author":"Liu","year":"2019","journal-title":"arXiv"},{"key":"B12","unstructured":"Macias\n              P.\n            \n            \n              Stelmasiak\n              D.\n            \n          \n          Warszawa\n          Narodowy Bank Polski\n          Food Inflation Nowcasting With Web Scraped Data\n          \n          2019"},{"key":"B13","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1016\/j.ijforecast.2012.12.003","article-title":"Now-casting inflation using high frequency data","volume":"29","author":"Modugno","year":"2013","journal-title":"Int. J. Forecast"},{"key":"B14","doi-asserted-by":"publisher","first-page":"106490","DOI":"10.1016\/j.knosys.2020.106490","article-title":"Imbalance accuracy metric for model selection in multi-class imbalance classification problems","volume":"210","author":"Mortaz","year":"2020","journal-title":"Knowl. Based Syst"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2003.02912","article-title":"What the [mask]? Making sense of language-specific bert models","author":"Nozza","year":"2020","journal-title":"arXiv"},{"key":"B16","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/j.1751-5823.1999.tb00451.x","article-title":"Measurement biases in consumer price indexes","volume":"67","author":"White","year":"1999","journal-title":"Int. Statist. Rev"},{"key":"B17","doi-asserted-by":"crossref","DOI":"10.1108\/S1477-407020140000010015","volume-title":"Comparison of Technological Performance Between Digital Single-Lens Reflex Cameras and Mirrorless Cameras","author":"Yoon","year":"2014"}],"container-title":["Frontiers in Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/frai.2025.1520659\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T05:21:09Z","timestamp":1744176069000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/frai.2025.1520659\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,9]]},"references-count":17,"alternative-id":["10.3389\/frai.2025.1520659"],"URL":"https:\/\/doi.org\/10.3389\/frai.2025.1520659","relation":{},"ISSN":["2624-8212"],"issn-type":[{"value":"2624-8212","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,9]]},"article-number":"1520659"}}