{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T09:14:50Z","timestamp":1743066890954,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031188398"},{"type":"electronic","value":"9783031188404"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-18840-4_15","type":"book-chapter","created":{"date-parts":[[2022,11,5]],"date-time":"2022-11-05T07:04:51Z","timestamp":1667631891000},"page":"197-211","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Data-Driven Prediction of\u00a0Athletes\u2019 Performance Based on\u00a0Their Social Media Presence"],"prefix":"10.1007","author":[{"given":"Frank","family":"Dreyer","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jannik","family":"Greif","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kolja","family":"G\u00fcnther","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Myra","family":"Spiliopoulou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Uli","family":"Niemann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,6]]},"reference":[{"key":"15_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0065-2601(08)60211-7","volume":"19","author":"RS Baron","year":"1986","unstructured":"Baron, R.S.: Distraction-conflict theory: progress and problems. Adv. Exp. Soc. Psychol. 19, 1\u201340 (1986). https:\/\/doi.org\/10.1016\/S0065-2601(08)60211-7","journal-title":"Adv. Exp. Soc. Psychol."},{"key":"15_CR2","doi-asserted-by":"publisher","unstructured":"Barrie, C., Chun-ting Ho, J.: academictwitteR: an R package to access the twitter academic research product track v2 API endpoint. J. Open Source Softw. 6(62), 3272 (2021). https:\/\/doi.org\/10.21105\/joss.03272","DOI":"10.21105\/joss.03272"},{"issue":"1","key":"15_CR3","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forest. Mach. Learn. 45(1), 5\u201332 (2001). https:\/\/doi.org\/10.1023\/A:1010933404324","journal-title":"Mach. Learn."},{"issue":"14","key":"15_CR4","doi-asserted-by":"publisher","first-page":"2499","DOI":"10.1080\/00949655.2020.1783262","volume":"90","author":"PC B\u00fcrkner","year":"2020","unstructured":"B\u00fcrkner, P.C., Gabry, J., Vehtari, A.: Approximate leave-future-out cross-validation for bayesian time series models. J. Stat. Comput. Simul. 90(14), 2499\u20132523 (2020). https:\/\/doi.org\/10.1080\/00949655.2020.1783262","journal-title":"J. Stat. Comput. Simul."},{"key":"15_CR5","doi-asserted-by":"publisher","unstructured":"Coleman, T., Peng, W., Mentch, L.: Scalable and efficient hypothesis testing with random forests (2019). https:\/\/doi.org\/10.48550\/arXiv.1904.07830","DOI":"10.48550\/arXiv.1904.07830"},{"key":"15_CR6","unstructured":"ESPN: vince carter addresses the negative effects of social media on athletes (2020). https:\/\/www.youtube.com\/watch?v=1cX5_2YadU4. Accessed 03 Mar 2022"},{"issue":"2","key":"15_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2938640","volume":"49","author":"A Giachanou","year":"2016","unstructured":"Giachanou, A., Crestani, F.: Like it or not: a survey of twitter sentiment analysis methods. ACM Comput. Surv. (CSUR) 49(2), 1\u201341 (2016). https:\/\/doi.org\/10.1145\/2938640","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"15_CR8","doi-asserted-by":"publisher","unstructured":"Gr\u00fcttner, A., Vitisvorakarn, M., Wambsganss, T., Rietsche, R., Back, A.: The new window to athletes\u2019 soul-what social media tells us about athletes\u2019 performances. In: Proceeding of Hawaii International Conference on System Sciences (HICSS), pp. 2479\u20132488 (2020). https:\/\/doi.org\/10.24251\/HICSS.2020.303","DOI":"10.24251\/HICSS.2020.303"},{"issue":"5","key":"15_CR9","doi-asserted-by":"publisher","first-page":"852","DOI":"10.1016\/j.smr.2019.12.006","volume":"23","author":"M Hayes","year":"2020","unstructured":"Hayes, M., Filo, K., Geurin, A., Riot, C.: An exploration of the distractions inherent to social media use among athletes. Sport Manage. Rev. 23(5), 852\u2013868 (2020). https:\/\/doi.org\/10.1016\/j.smr.2019.12.006","journal-title":"Sport Manage. Rev."},{"key":"15_CR10","doi-asserted-by":"crossref","unstructured":"Hutto, C., Gilbert, E.: VADER: a parsimonious rule-based model for sentiment analysis of social media text. In: Proceeding of AAAI Conference on Web and Social Media, vol. 8, pp. 216\u2013225 (2014). https:\/\/www.aaai.org\/ocs\/index.php\/ICWSM\/ICWSM14\/paper\/view\/8109\/8122","DOI":"10.1609\/icwsm.v8i1.14550"},{"issue":"4","key":"15_CR11","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1111\/j.1600-0838.1995.tb00035.x","volume":"5","author":"SE Iso-Ahola","year":"1995","unstructured":"Iso-Ahola, S.E.: Intrapersonal and interpersonal factors in athletic performance. Scandinavian J. Med. Sci. Sports 5(4), 191\u2013199 (1995). https:\/\/doi.org\/10.1111\/j.1600-0838.1995.tb00035.x","journal-title":"Scandinavian J. Med. Sci. Sports"},{"issue":"1","key":"15_CR12","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.sleh.2018.09.005","volume":"5","author":"JJ Jones","year":"2019","unstructured":"Jones, J.J., Kirschen, G.W., Kancharla, S., Hale, L.: Association between late-night tweeting and next-day game performance among professional basketball players. Sleep Health 5(1), 68\u201371 (2019). https:\/\/doi.org\/10.1016\/j.sleh.2018.09.005","journal-title":"Sleep Health"},{"key":"15_CR13","doi-asserted-by":"publisher","unstructured":"Lim, J.H., Donovan, L.A.N., Kaufman, P., Ishida, C.: Professional athletes\u2019 social media use and player performance: evidence from the national football league. Int. J. Sport Commun. 14(1), 1\u201327 (2020). https:\/\/doi.org\/10.1123\/ijsc.2020-0055","DOI":"10.1123\/ijsc.2020-0055"},{"issue":"1","key":"15_CR14","first-page":"841","volume":"17","author":"L Mentch","year":"2016","unstructured":"Mentch, L., Hooker, G.: Quantifying uncertainty in random forests via confidence intervals and hypothesis tests. J. Mach. Learn. Res. 17(1), 841\u2013881 (2016)","journal-title":"J. Mach. Learn. Res."},{"key":"15_CR15","unstructured":"Myers, D.: About Box Plus\/Minus (BPM) (2020). https:\/\/www.basketball-reference.com\/about\/bpm2.html. Accessed 12 Mar 2022"},{"key":"15_CR16","doi-asserted-by":"crossref","unstructured":"Nguyen, D.Q., Vu, T., Nguyen, A.T.: BERTweet: a pre-trained language model for english tweets (2020). https:\/\/arxiv.org\/abs\/2005.10200","DOI":"10.18653\/v1\/2020.emnlp-demos.2"},{"key":"15_CR17","unstructured":"von Ott, K., Puymbroeck, M.V.: Does the media impact athletic performance. Sport J. 9(3), (2006)"},{"key":"15_CR18","unstructured":"Rinker, T.W.: Textclean: text cleaning tools. Buffalo, New York (2018). https:\/\/github.com\/trinker\/textclean, version 0.9.3"},{"issue":"9","key":"15_CR19","doi-asserted-by":"publisher","first-page":"6279","DOI":"10.1007\/s11042-019-08291-9","volume":"79","author":"D Rousidis","year":"2020","unstructured":"Rousidis, D., Koukaras, P., Tjortjis, C.: Social media prediction: a literature review. Multimedia Tools Appl. 79(9), 6279\u20136311 (2020). https:\/\/doi.org\/10.1007\/s11042-019-08291-9","journal-title":"Multimedia Tools Appl."},{"key":"15_CR20","doi-asserted-by":"publisher","unstructured":"Snijders, T.A.: On cross-validation for predictor evaluation in time series. In: On Model Uncertainty and its Statistical Implications, pp. 56\u201369. Springer (1988). https:\/\/doi.org\/10.1007\/978-3-642-61564-1_4","DOI":"10.1007\/978-3-642-61564-1_4"},{"issue":"1","key":"15_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2105-8-25","volume":"8","author":"C Strobl","year":"2007","unstructured":"Strobl, C., Boulesteix, A.L., Zeileis, A., Hothorn, T.: Bias in random forest variable importance measures: illustrations, sources and a solution. BMC Bioinformatics 8(1), 1\u201321 (2007). https:\/\/doi.org\/10.1186\/1471-2105-8-25","journal-title":"BMC Bioinformatics"},{"key":"15_CR22","doi-asserted-by":"publisher","unstructured":"Watkins, R.A., Sugimoto, D., Hunt, D.L., Oldham, J.R., Stracciolini, A.: The impact of social media use on sleep quality and performance among collegiate athletes. Orthop. J. Sports Med. 9(7_suppl3) (2021). https:\/\/doi.org\/10.1177\/2325967121S00087","DOI":"10.1177\/2325967121S00087"},{"key":"15_CR23","unstructured":"Wright, M.N., Ziegler, A.: ranger: a fast implementation of random forests for high dimensional data in C++ and R. arXiv preprint arXiv:1508.04409 (2015). https:\/\/arxiv.org\/abs\/1508.04409"},{"key":"15_CR24","doi-asserted-by":"publisher","unstructured":"Xu, C., Yu, Y.: Measuring NBA players\u2019 mood by mining athlete-generated content. In: Proceeding of Hawaii International Conference on System Sciences (HICSS), pp. 1706\u20131713. IEEE (2015). https:\/\/doi.org\/10.1109\/HICSS.2015.205","DOI":"10.1109\/HICSS.2015.205"}],"container-title":["Lecture Notes in Computer Science","Discovery Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-18840-4_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,5]],"date-time":"2022-11-05T07:06:42Z","timestamp":1667632002000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-18840-4_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031188398","9783031188404"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-18840-4_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"6 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Discovery Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Montpellier","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dis2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ds2022.sciencesconf.org\/","order":11,"name":"conference_url","label":"Conference URL","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":"59","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":"27","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":"12","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":"46% - 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":"2.5","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":"2.5","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)"}}]}}