{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T23:49:56Z","timestamp":1742946596688,"version":"3.40.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030377199"},{"type":"electronic","value":"9783030377205"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-37720-5_8","type":"book-chapter","created":{"date-parts":[[2020,1,3]],"date-time":"2020-01-03T05:26:59Z","timestamp":1578029219000},"page":"101-106","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Monitoring the Business Cycle with Fine-Grained, Aspect-Based Sentiment Extraction from News"],"prefix":"10.1007","author":[{"given":"Luca","family":"Barbaglia","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7357-5858","authenticated-orcid":false,"given":"Sergio","family":"Consoli","sequence":"additional","affiliation":[]},{"given":"Sebastiano","family":"Manzan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,1,3]]},"reference":[{"key":"8_CR1","doi-asserted-by":"publisher","first-page":"85","DOI":"10.3905\/jpm.2018.44.7.085","volume":"44","author":"S Agrawal","year":"2018","unstructured":"Agrawal, S., Azar, P., Lo, A.W., Singh, T.: Momentum, mean-reversion and social media: evidence from StockTwits and Twitter. J. Portf. Manag. 44, 85\u201395 (2018)","journal-title":"J. Portf. Manag."},{"key":"8_CR2","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1007\/978-3-319-25518-7_4","volume":"548","author":"S Consoli","year":"2015","unstructured":"Consoli, S., Recupero, D.R.: Using FRED for named entity resolution, linking and typing for knowledge base population. Commun. Comput. Inform. Sci. 548, 40\u201350 (2015)","journal-title":"Commun. Comput. Inform. Sci."},{"issue":"8","key":"8_CR3","doi-asserted-by":"publisher","first-page":"2199","DOI":"10.1007\/s13042-018-0805-x","volume":"10","author":"A Dridi","year":"2019","unstructured":"Dridi, A., Atzeni, M., Recupero, D.R.: FineNews: fine-grained semantic sentiment analysis on financial microblogs and news. Int. J. Mach. Learn. Cybern. 10(8), 2199\u20132207 (2019)","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"8_CR4","unstructured":"Fabbi, C., Righi, A., Testa, P., Valentino, L., Zardetto, D.: Social mood on economy index. In: XIII Conferenza Nazionale di Statistica (2018)"},{"key":"8_CR5","doi-asserted-by":"crossref","unstructured":"Gentzkow, M., Kelly, B., Taddy, M.: Text as data. J. Econ. Lit. (2019, to appear)","DOI":"10.1257\/jel.20181020"},{"key":"8_CR6","doi-asserted-by":"publisher","first-page":"S114","DOI":"10.1016\/j.jinteco.2015.12.008","volume":"99","author":"S Hansen","year":"2016","unstructured":"Hansen, S., McMahon, M.: Shocking language: understanding the macroeconomic effects of central bank communication. J. Int. Econ. 99, S114\u2013S133 (2016)","journal-title":"J. Int. Econ."},{"key":"8_CR7","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s12559-014-9302-z","volume":"7","author":"DR Recupero","year":"2015","unstructured":"Recupero, D.R., Presutti, V., Consoli, S., Gangemi, A., Nuzzolese, A.G.: Sentilo: frame-based sentiment analysis. Cogn. Comput. 7, 211\u2013225 (2015)","journal-title":"Cogn. Comput."},{"key":"8_CR8","doi-asserted-by":"crossref","unstructured":"Shapiro, A.H., Sudhof, M., Wilson, D.: Measuring news sentiment. Federal Reserve Bank of San Francisco Working Paper (2018)","DOI":"10.24148\/erwp2017-01"},{"issue":"3","key":"8_CR9","doi-asserted-by":"publisher","first-page":"1139","DOI":"10.1111\/j.1540-6261.2007.01232.x","volume":"62","author":"PC Tetlock","year":"2007","unstructured":"Tetlock, P.C.: Giving content to investor sentiment: the role of media in the stock market. J. Financ. 62(3), 1139\u20131168 (2007)","journal-title":"J. Financ."},{"key":"8_CR10","doi-asserted-by":"crossref","unstructured":"Thorsrud, L.A.: Nowcasting using news topics. big data versus big bank. Norges Bank Working Paper (2016)","DOI":"10.2139\/ssrn.2901450"},{"key":"8_CR11","unstructured":"Thorsrud, L.A.: Words are the new numbers: a newsy coincident index of the business cycle. J. Bus. Econ. Stat. 1\u201317 (2018, in press)"},{"key":"8_CR12","doi-asserted-by":"crossref","unstructured":"Tuckett, D.: Conviction narrative theory and understanding decision-making in economics and finance. In: Uncertain Futures: Imaginaries, Narratives, and Calculation in the Economy, pp. 62\u201382 (2018)","DOI":"10.1093\/oso\/9780198820802.003.0003"}],"container-title":["Lecture Notes in Computer Science","Mining Data for Financial Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-37720-5_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,3]],"date-time":"2025-01-03T00:08:20Z","timestamp":1735862900000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-37720-5_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030377199","9783030377205"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-37720-5_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"3 January 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MIDAS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Workshop on Mining Data for Financial Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"W\u00fcrzburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"midas2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"16","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"8","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"50% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}