{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T14:43:37Z","timestamp":1781707417996,"version":"3.54.5"},"publisher-location":"Singapore","reference-count":18,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789811982330","type":"print"},{"value":"9789811982347","type":"electronic"}],"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\/978-981-19-8234-7_16","type":"book-chapter","created":{"date-parts":[[2022,11,23]],"date-time":"2022-11-23T07:05:58Z","timestamp":1669187158000},"page":"201-213","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Forecasting Cryptocurrency Price Fluctuations with\u00a0Granger Causality Analysis"],"prefix":"10.1007","author":[{"given":"David L.","family":"John","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bela","family":"Stantic","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,11,24]]},"reference":[{"key":"16_CR1","unstructured":"AliciaAdamczyk: What\u2019s behind dogecoin\u2019s price surge and why seemingly unrelated brands are capitalizing on its popularity (2021). https:\/\/www.cnbc.com\/2021\/05\/12\/dogecoin-price-surge-elon-musk-slim-jim.html"},{"issue":"1","key":"16_CR2","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1080\/13683500.2015.1073231","volume":"20","author":"M Bilen","year":"2017","unstructured":"Bilen, M., Yilanci, V., Ery\u00fczl\u00fc, H.: Tourism development and economic growth: a panel granger causality analysis in the frequency domain. Curr. Issue Tour. 20(1), 27\u201332 (2017)","journal-title":"Curr. Issue Tour."},{"issue":"1","key":"16_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jocs.2010.12.007","volume":"2","author":"J Bollen","year":"2011","unstructured":"Bollen, J., Mao, H., Zeng, X.: Twitter mood predicts the stock market. J. Comput. Sci. 2(1), 1\u20138 (2011). https:\/\/doi.org\/10.1016\/j.jocs.2010.12.007","journal-title":"J. Comput. Sci."},{"key":"16_CR4","unstructured":"Brooks, C.: What is statistical analysis? (2020). https:\/\/www.businessnewsdaily.com\/6000-statistical-analysis.html"},{"issue":"2","key":"16_CR5","doi-asserted-by":"publisher","first-page":"639","DOI":"10.2298\/CSIS181015013C","volume":"16","author":"J Chen","year":"2019","unstructured":"Chen, J., Becken, S., Stantic, B.: Lexicon based Chinese language sentiment analysis method. Comput. Sci. Inf. Syst. 16(2), 639\u2013655 (2019)","journal-title":"Comput. Sci. Inf. Syst."},{"issue":"7","key":"16_CR6","doi-asserted-by":"publisher","first-page":"1351","DOI":"10.1016\/j.jbankfin.2009.02.013","volume":"33","author":"CC Chuang","year":"2009","unstructured":"Chuang, C.C., Kuan, C.M., Lin, H.Y.: Causality in quantiles and dynamic stock return-volume relations. J. Bank. Financ. 33(7), 1351\u20131360 (2009). https:\/\/doi.org\/10.1016\/j.jbankfin.2009.02.013","journal-title":"J. Bank. Financ."},{"key":"16_CR7","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/9609.001.0001","volume-title":"Analyzing Neural Time Series Data: Theory and Practice","author":"MX Cohen","year":"2014","unstructured":"Cohen, M.X.: Analyzing Neural Time Series Data: Theory and Practice. MIT press, Cambridge (2014)"},{"key":"16_CR8","unstructured":"Wikimedia Commons: File:GrangerCausalityIllustration.svg (2014). https:\/\/commons.wikimedia.org\/wiki\/File:GrangerCausalityIllustration.svg"},{"key":"16_CR9","unstructured":"Dillard, J.: 5 most important methods for statistical data analysis (2015). https:\/\/www.bigskyassociates.com\/blog\/bid\/356764\/5-Most-Important-Methods-For-Statistical-Data-Analysis"},{"key":"16_CR10","unstructured":"Encyclopedia: International encyclopedia of the social sciences (2021). https:\/\/www.encyclopedia.com\/social-sciences\/applied-and-social-sciences-magazines\/autoregressive-models"},{"key":"16_CR11","doi-asserted-by":"publisher","first-page":"424","DOI":"10.2307\/1912791","volume":"37","author":"CW Granger","year":"1969","unstructured":"Granger, C.W.: Investigating causal relations by econometric models and cross-spectral methods. J. Econom. Soc. 37, 424\u2013438 (1969)","journal-title":"J. Econom. Soc."},{"issue":"3","key":"16_CR12","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1016\/j.dss.2013.02.006","volume":"55","author":"M Hagenau","year":"2013","unstructured":"Hagenau, M., Liebmann, M., Neumann, D.: Automated news reading: stock price prediction based on financial news using context-capturing features. Decis. Support Syst. 55(3), 685\u2013697 (2013). https:\/\/doi.org\/10.1016\/j.dss.2013.02.006","journal-title":"Decis. Support Syst."},{"key":"16_CR13","first-page":"451","volume":"12","author":"D Hendry","year":"2013","unstructured":"Hendry, D., Ter\u00e4svirta, T.: Sir Clive William John Granger 1934\u20132009. Biogr. Mem. Fellows Br. Acad. 12, 451\u2013469 (2013)","journal-title":"Biogr. Mem. Fellows Br. Acad."},{"key":"16_CR14","doi-asserted-by":"crossref","unstructured":"Hutto, C., Gilbert, E.: VADER: a parsimonious rule-based model for sentiment analysis of social media text. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8, pp. 216\u2013225 (2014)","DOI":"10.1609\/icwsm.v8i1.14550"},{"issue":"1","key":"16_CR15","doi-asserted-by":"publisher","first-page":"7","DOI":"10.24136\/oc.2019.001","volume":"10","author":"M Skare","year":"2019","unstructured":"Skare, M., Porada-Rocho\u0144, M.: Financial and economic development link in transitional economies: a spectral granger causality analysis 1991\u20132017. Oecon. Copernic. 10(1), 7\u201335 (2019)","journal-title":"Oecon. Copernic."},{"issue":"3","key":"16_CR16","doi-asserted-by":"publisher","first-page":"625","DOI":"10.1111\/j.1467-9361.2010.00578.x","volume":"14","author":"WH Tsen","year":"2010","unstructured":"Tsen, W.H.: Exports, domestic demand, and economic growth in China: Granger causality analysis. Rev. Dev. Econ. 14(3), 625\u2013639 (2010)","journal-title":"Rev. Dev. Econ."},{"key":"16_CR17","unstructured":"Wei, W.: Granger causality test (2016). https:\/\/www.sciencedirect.com\/topics\/social-sciences\/granger-causality-test"},{"key":"16_CR18","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.frl.2017.07.018","volume":"23","author":"W You","year":"2017","unstructured":"You, W., Guo, Y., Peng, C.: Twitter\u2019s daily happiness sentiment and the predictability of stock returns. Financ. Res. Lett. 23, 58\u201364 (2017). https:\/\/doi.org\/10.1016\/j.frl.2017.07.018","journal-title":"Financ. Res. Lett."}],"container-title":["Communications in Computer and Information Science","Recent Challenges in Intelligent Information and Database Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-19-8234-7_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,23]],"date-time":"2022-11-23T07:10:25Z","timestamp":1669187425000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-19-8234-7_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811982330","9789811982347"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-981-19-8234-7_16","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"24 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACIIDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asian Conference on Intelligent Information and Database Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ho Chi Minh City","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","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":"28 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aciids2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aciids.pwr.edu.pl\/2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}