{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T10:26:14Z","timestamp":1773656774888,"version":"3.50.1"},"reference-count":67,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004836","name":"Det Frie Forskningsr\u00e5d","doi-asserted-by":"publisher","award":["9131-00115B"],"award-info":[{"award-number":["9131-00115B"]}],"id":[{"id":"10.13039\/501100004836","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010663","name":"H2020 European Research Council","doi-asserted-by":"publisher","award":["725706"],"award-info":[{"award-number":["725706"]}],"id":[{"id":"10.13039\/100010663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Big Data &amp; Society"],"published-print":{"date-parts":[[2022,1]]},"abstract":"<jats:p> Social media commentary, satellite imagery and GPS data are a part of \u2018alternative data\u2019, that is, data that originate outside of the standard repertoire of market data but are considered useful for predicting stock prices, detecting different risk exposures and discovering new price movement indicators. With the availability of sophisticated machine-learning analytics tools, alternative data are gaining traction within the investment management and algorithmic trading industries. Drawing on interviews with people working in investment management and algorithmic trading firms utilizing alternative data, as well as firms providing and sourcing such data, we emphasize social media-based sentiment analytics as one manifestation of how alternative data are deployed for stock price prediction purposes. This demonstrates both how sentiment analytics are developed and subsequently utilized by investment management firms. We argue that \u2018alternative data\u2019 are an open-ended placeholder for every data source potentially relevant for investment management purposes and harnessing these disparate data sources requires certain standardization efforts by different market participants. Besides showing how market participants understand and use alternative data, we demonstrate that alternative data often undergo processes of (a) prospecting (i.e. rendering such data amenable to processing with the aid of analytics tools) and (b) assetization (i.e. the transformation of data into tradable assets). We further contend that the widespread embracement of alternative data in investment management and trading encourages a financialization process at the data level which raises new governance issues. <\/jats:p>","DOI":"10.1177\/20539517211070701","type":"journal-article","created":{"date-parts":[[2022,1,20]],"date-time":"2022-01-20T12:58:06Z","timestamp":1642683486000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":50,"title":["Alternative data and sentiment analysis: Prospecting non-standard data in machine learning-driven finance"],"prefix":"10.1177","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9536-6050","authenticated-orcid":false,"given":"Kristian Bondo","family":"Hansen","sequence":"first","affiliation":[{"name":"Department of Management, Society and Communication, Copenhagen Business School, Frederiksberg, Denmark"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8217-5880","authenticated-orcid":false,"given":"Christian","family":"Borch","sequence":"additional","affiliation":[{"name":"Department of Management, Politics and Philosophy, Copenhagen Business School, Frederiksberg, Denmark"}]}],"member":"179","published-online":{"date-parts":[[2022,1,20]]},"reference":[{"key":"bibr1-20539517211070701","unstructured":"Ade-Ojo J (2021) Using the WallStreetBets subreddit to gain insights on historic stock market trends. 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