{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T23:52:31Z","timestamp":1742946751518,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":27,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811528095"},{"type":"electronic","value":"9789811528101"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-981-15-2810-1_34","type":"book-chapter","created":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T18:03:11Z","timestamp":1580580191000},"page":"350-361","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Novel Way to Build Stock Market Sentiment Lexicon"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1611-7206","authenticated-orcid":false,"given":"Yangcheng","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0041-3158","authenticated-orcid":false,"given":"Fawaz E.","family":"Alsaadi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,2,2]]},"reference":[{"issue":"3","key":"34_CR1","doi-asserted-by":"publisher","first-page":"1259","DOI":"10.1111\/j.1540-6261.2004.00662.x","volume":"59","author":"W Antweiler","year":"2004","unstructured":"Antweiler, W., Frank, M.Z.: Is all that talk just noise? The information content of internet stock message boards. J. Finan. 59(3), 1259\u20131294 (2004). \nhttps:\/\/doi.org\/10.1111\/j.1540-6261.2004.00662.x","journal-title":"J. Finan."},{"issue":"1","key":"34_CR2","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., et al.: Twitter mood predicts the stock market. J. Comput. Sci. 2(1), 1\u20138 (2011). \nhttps:\/\/doi.org\/10.1016\/j.jocs.2010.12.007","journal-title":"J. Comput. Sci."},{"issue":"1","key":"34_CR3","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1186\/S40854-018-0107-Z","volume":"4","author":"ML Challa","year":"2018","unstructured":"Challa, M.L., et al.: Forecasting risk using auto regressive integrated moving average approach: an evidence from S&P BSE Sensex. Finan. Innov. 4(1), 24 (2018). \nhttps:\/\/doi.org\/10.1186\/S40854-018-0107-Z","journal-title":"Finan. Innov."},{"key":"34_CR4","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1007\/1-4020-4102-0_22","volume-title":"Computing Attitude and Affect in Text: Theory and Applications","author":"M Koppel","year":"2006","unstructured":"Koppel, M., Shtrimberg, I.: Good news or bad news? Let the market decide. In: Shanahan, J.G., et al. (eds.) Computing Attitude and Affect in Text: Theory and Applications, pp. 297\u2013301. Springer, Dordrecht (2006). \nhttps:\/\/doi.org\/10.1007\/1-4020-4102-0_22"},{"key":"34_CR5","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.dss.2014.01.013","volume":"61","author":"Q Li","year":"2014","unstructured":"Li, Q., et al.: Media-aware quantitative trading based on public Web information. Decis. Support Syst. 61, 93\u2013105 (2014). \nhttps:\/\/doi.org\/10.1016\/j.dss.2014.01.013","journal-title":"Decis. Support Syst."},{"key":"34_CR6","doi-asserted-by":"publisher","first-page":"826","DOI":"10.1016\/j.ins.2014.03.096","volume":"278","author":"Q Li","year":"2014","unstructured":"Li, Q., et al.: The effect of news and public mood on stock movements. Inf. Sci. 278, 826\u2013840 (2014). \nhttps:\/\/doi.org\/10.1016\/j.ins.2014.03.096","journal-title":"Inf. Sci."},{"issue":"1","key":"34_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00416ED1V01Y201204HLT016","volume":"5","author":"B Liu","year":"2012","unstructured":"Liu, B.: Sentiment analysis and opinion mining. Synth. Lect. Hum. Lang. Technol. 5(1), 1\u2013167 (2012). \nhttps:\/\/doi.org\/10.2200\/S00416ED1V01Y201204HLT016","journal-title":"Synth. Lect. Hum. Lang. Technol."},{"key":"34_CR8","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.ins.2017.02.016","volume":"394\u2013395","author":"Y Liu","year":"2017","unstructured":"Liu, Y., et al.: A method for multi-class sentiment classification based on an improved one-vs-one (OVO) strategy and the support vector machine (SVM) algorithm. Inf. Sci. 394\u2013395, 38\u201352 (2017). \nhttps:\/\/doi.org\/10.1016\/j.ins.2017.02.016","journal-title":"Inf. Sci."},{"issue":"6","key":"34_CR9","doi-asserted-by":"publisher","first-page":"1497","DOI":"10.1142\/S021962201750033X","volume":"16","author":"Y Liu","year":"2017","unstructured":"Liu, Y., et al.: A method for ranking products through online reviews based on sentiment classification and interval-valued intuitionistic fuzzy TOPSIS. Int. J. Inf. Tech. Decis. Making 16(6), 1497\u20131522 (2017). \nhttps:\/\/doi.org\/10.1142\/S021962201750033X","journal-title":"Int. J. Inf. Tech. Decis. Making"},{"issue":"1","key":"34_CR10","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1111\/j.1540-6261.2010.01625.x","volume":"66","author":"T Loughran","year":"2011","unstructured":"Loughran, T., Mcdonald, B.: When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks. J. Finan. 66(1), 35\u201365 (2011). \nhttps:\/\/doi.org\/10.1111\/j.1540-6261.2010.01625.x","journal-title":"J. Finan."},{"issue":"3","key":"34_CR11","doi-asserted-by":"publisher","first-page":"883","DOI":"10.1142\/S0219622018500128","volume":"17","author":"PD Mahendhiran","year":"2018","unstructured":"Mahendhiran, P.D., Kannimuthu, S.: Deep learning techniques for polarity classification in multimodal sentiment analysis. Int. J. Inf. Tech. Decis. Making 17(3), 883\u2013910 (2018). \nhttps:\/\/doi.org\/10.1142\/S0219622018500128","journal-title":"Int. J. Inf. Tech. Decis. Making"},{"issue":"2","key":"34_CR12","first-page":"1","volume":"20","author":"H Mao","year":"2014","unstructured":"Mao, H., et al.: Automatic construction of financial semantic orientation lexicon from large-scale Chinese news corpus. Institut Louis Bachelier 20(2), 1\u201318 (2014)","journal-title":"Institut Louis Bachelier"},{"issue":"1","key":"34_CR13","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1186\/S40854-018-0104-2","volume":"4","author":"SC Nayak","year":"2018","unstructured":"Nayak, S.C., Misra, B.B.: Estimating stock closing indices using a GA-weighted condensed polynomial neural network. Finan. Innov. 4(1), 21 (2018). \nhttps:\/\/doi.org\/10.1016\/j.dss.2016.02.013","journal-title":"Finan. Innov."},{"key":"34_CR14","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.dss.2016.02.013","volume":"85","author":"N Oliveira","year":"2016","unstructured":"Oliveira, N., et al.: Stock market sentiment lexicon acquisition using microblogging data and statistical measures. Decis. Support Syst. 85, 62\u201373 (2016). \nhttps:\/\/doi.org\/10.1186\/S40854-018-0104-2","journal-title":"Decis. Support Syst."},{"issue":"2","key":"34_CR15","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1162\/coli.2009.35.2.311","volume":"35","author":"B Pang","year":"2009","unstructured":"Pang, B., Lee, L.: Opinion mining and sentiment analysis. Comput. Linguist. 35(2), 311\u2013312 (2009). \nhttps:\/\/doi.org\/10.1162\/coli.2009.35.2.311","journal-title":"Comput. Linguist."},{"issue":"1","key":"34_CR16","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/S40854-018-0100-6","volume":"4","author":"A Rashid","year":"2018","unstructured":"Rashid, A., Jabeen, N.: Financial frictions and the cash flow \u2013 external financing sensitivity: evidence from a panel of Pakistani firms. Finan. Innov. 4(1), 15 (2018). \nhttps:\/\/doi.org\/10.1186\/S40854-018-0100-6","journal-title":"Finan. Innov."},{"key":"34_CR17","doi-asserted-by":"publisher","unstructured":"Rosenthal, S., et al.: SemEval-2014 task 9: sentiment analysis in Twitter. In: Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), pp. 73\u201380. Association for Computational Linguistics (2015). \nhttps:\/\/doi.org\/10.3115\/V1\/S14-2009","DOI":"10.3115\/V1\/S14-2009"},{"issue":"3","key":"34_CR18","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1016\/j.dss.2012.03.001","volume":"53","author":"RP Schumaker","year":"2012","unstructured":"Schumaker, R.P., et al.: Evaluating sentiment in financial news articles. Decis. Support Syst. 53(3), 458\u2013464 (2012). \nhttps:\/\/doi.org\/10.1016\/j.dss.2012.03.001","journal-title":"Decis. Support Syst."},{"key":"34_CR19","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1145\/1462198.1462204","volume":"27","author":"RP Schumaker","year":"2009","unstructured":"Schumaker, R.P., Chen, H.: Textual analysis of stock market prediction using breaking financial news: the AZFin text system. ACM Trans. Inf. Syst. 27, 29 (2009)","journal-title":"ACM Trans. Inf. Syst."},{"issue":"2","key":"34_CR20","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1257\/jep.4.2.19","volume":"4","author":"A Shleifer","year":"1990","unstructured":"Shleifer, A., Summers, L.H.: The noise trader approach to finance. J. Econ. Perspect. 4(2), 19\u201333 (1990). \nhttps:\/\/doi.org\/10.1257\/jep.4.2.19","journal-title":"J. Econ. Perspect."},{"key":"34_CR21","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1016\/j.dss.2014.07.003","volume":"66","author":"NFF Silva da","year":"2014","unstructured":"da Silva, N.F.F., et al.: Tweet sentiment analysis with classifier ensembles. Decis. Support Syst. 66, 170\u2013179 (2014). \nhttps:\/\/doi.org\/10.1016\/j.dss.2014.07.003","journal-title":"Decis. Support Syst."},{"issue":"1","key":"34_CR22","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1186\/S40854-018-0086-0","volume":"4","author":"Y Song","year":"2018","unstructured":"Song, Y., et al.: Sustainable strategy for corporate governance based on the sentiment analysis of financial reports with CSR. Finan. Innov. 4(1), 2 (2018). \nhttps:\/\/doi.org\/10.1186\/S40854-018-0086-0","journal-title":"Finan. Innov."},{"issue":"3","key":"34_CR23","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1007\/s00779-018-1121-x","volume":"22","author":"Y Sun","year":"2018","unstructured":"Sun, Y., et al.: A novel stock recommendation system using Guba sentiment analysis. Pers. Ubiquit. Comput. 22(3), 575\u2013587 (2018). \nhttps:\/\/doi.org\/10.1007\/s00779-018-1121-x","journal-title":"Pers. Ubiquit. Comput."},{"issue":"4","key":"34_CR24","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1145\/944012.944013","volume":"21","author":"PD Turney","year":"2003","unstructured":"Turney, P.D., Littman, M.L.: Measuring praise and criticism: inference of semantic orientation from association. ACM Trans. Inf. Syst. 21(4), 315\u2013346 (2003). \nhttps:\/\/doi.org\/10.1145\/944012.944013","journal-title":"ACM Trans. Inf. Syst."},{"issue":"02","key":"34_CR25","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1142\/S0219622019500068","volume":"18","author":"N Wang","year":"2019","unstructured":"Wang, N., et al.: Textual sentiment of Chinese microblog toward the stock market. Int. J. Inf. Technol. Decis. Making (IJITDM) 18(02), 649\u2013671 (2019). \nhttps:\/\/doi.org\/10.1142\/S0219622019500068","journal-title":"Int. J. Inf. Technol. Decis. Making (IJITDM)"},{"issue":"1","key":"34_CR26","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1186\/S40854-018-0098-9","volume":"4","author":"I Yousaf","year":"2018","unstructured":"Yousaf, I., et al.: Herding behavior in Ramadan and financial crises: the case of the Pakistani stock market. Finan. Innov. 4(1), 16 (2018). \nhttps:\/\/doi.org\/10.1186\/S40854-018-0098-9","journal-title":"Finan. Innov."},{"key":"34_CR27","doi-asserted-by":"publisher","unstructured":"Yuen, R.W.M., et al.: Morpheme-based derivation of bipolar semantic orientation of Chinese words. In: Proceedings of the 20th International Conference on Computational Linguistics. Association for Computational Linguistics, Stroudsburg (2004). \nhttps:\/\/doi.org\/10.3115\/1220355.1220500","DOI":"10.3115\/1220355.1220500"}],"container-title":["Communications in Computer and Information Science","Data Science"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-2810-1_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,4,25]],"date-time":"2020-04-25T10:06:49Z","timestamp":1587809209000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-15-2810-1_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9789811528095","9789811528101"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-2810-1_34","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"2 February 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Data Service","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"15 May 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 May 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icds2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/vcrab.com.au\/ICDS2019\/home.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Open","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":"210","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":"64","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":"0","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":"30% - 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":"14","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)"}}]}}