Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 8/2019

10.03.2018 | Original Article

FineNews: fine-grained semantic sentiment analysis on financial microblogs and news

verfasst von: Amna Dridi, Mattia Atzeni, Diego Reforgiato Recupero

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 8/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In this paper, a fine-grained supervised approach is proposed to identify bullish and bearish sentiments associated with companies and stocks, by predicting a real-valued score between − 1 and + 1. We propose a supervised approach learned by using several feature sets, consisting of lexical features, semantic features and a combination of lexical and semantic features. Our study reveals that semantic features, most notably BabelNet synsets and semantic frames, can be successfully applied for Sentiment Analysis within the financial domain to achieve better results. Moreover, a comparative study has been conducted between our supervised approach and unsupervised approaches. The obtained experimental results show how our approach outperforms the others.
Vorheriger Artikel Dynamic optimisation based fuzzy association rule mining method
Nächster Artikel Factorization-based primary dimension modelling for multidimensional data in recommender systems

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Weitere Produktempfehlungen anzeigen
Fußnoten
Literatur
1.
Mostafa MM (2013) More than words: social networks’ text mining for consumer brand sentiments. Expert Syst. Appl. 40(10):4241–4251CrossRef
2.
O’Hare N, Davy M, Bermingham A, Ferguson P, Sheridan P, Gurrin C, Smeaton AF (2009) Topic-dependent sentiment analysis of financial blogs. In: Proceedings of the 1st international CIKM workshop on topic-sentiment analysis for mass opinion, TSA ’09, ACM, New York, pp 9–16
3.
Ghiassi M, Skinner J, Zimbra D (2013) Twitter brand sentiment analysis: a hybrid system using N-gram analysis and dynamic artificial neural network. Expert Syst Appl 40(16):6266–6282CrossRef
4.
Paul F, Neil O, Michael D, Adam B, Scott T, Paraic S, Cathal G, Alan FS (2009) Exploring the use of paragraph-level annotations for sentiment analysis of financial blogs. In: Proceedings of the 1st workshop on opinion mining and sentiment analysis, WOMSA 2009, pp 42–52
5.
Van de Kauter M, Breesch D, Hoste V (2015) Fine-grained analysis of explicit and implicit sentiment in financial news articles. Expert Syst. Appl 42(11):4999–5010CrossRef
6.
Raina P (2013) Sentiment analysis in news articles using sentic computing. In: Proceedings of the 2013 IEEE 13th international conference on data mining workshops, ICDMW ’13, IEEE Computer Society, Washington, DC, pp 959–962
7.
Fellbaum C (ed) (1998) WordNet: an electronic lexical database. MIT Press, CambridgeMATH
8.
Khadjeh Nassirtoussi A, Aghabozorgi S, Ying Wah T, Ngo DCL (2015) Text mining of news-headlines for FOREX market prediction. Expert Syst Appl 42(1):306–324CrossRef
9.
Gangemi A, Alam M, Asprino L, Presutti V, Recupero DR (2016) Framester: a wide coverage linguistic linked data hub. In: EKAW 2016, Bologna, 19–23 Nov 2016, Proceedings, pp 239–254
10.
Baccianella S, Esuli A, Sebastiani F (2010) Sentiwordnet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining. In: Proceedings of LREC’10. European Language Resources Association (ELRA), Valletta, pp 2200–2204
11.
12.
Khadjeh Nassirtoussi A, Aghabozorgi S, Ying Wah T, Ngo DCL (2014) Review: text mining for market prediction: a systematic review. Expert Syst Appl 41(16):7653–7670CrossRef
13.
Sprenger TO, Tumasjan A, Sandner PG, Welpe IM (2014) Tweets and trades: the information content of stock microblogs. Eur Financ Manag 20(5):926–957CrossRef
14.
Du J, Xu H, Huang X (2014) Box office prediction based on microblog. Expert Syst Appl 41(4):1680–1689CrossRef
15.
Schulz A, Thanh TD, Paulheim H, Schweizer I (2013) A fine-grained sentiment analysis approach for detecting crisis related microposts. In: 10th proceedings of the international conference on information systems for crisis response and management, Baden-Baden, 12–15 May 2013, pp 846–851
16.
Li X, Xie H, Chen L, Wang J, Deng X (2014) News impact on stock price return via sentiment analysis. Knowl Based Syst 69(Supplement C):14–23CrossRef
17.
Loughran T, McDonald B (2011) When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks. J Finance 66(1):35–65CrossRef
18.
Li X, Xie H, Song Y, Zhu S, Li Q, Wang FL (2015) Does summarization help stock prediction? A news impact analysis. IEEE Intell Syst 30(3):26–34CrossRef
19.
Feuerriegel S, Ratku A, Neumann D (2016) Analysis of how underlying topics in financial news affect stock prices using latent Dirichlet allocation. In: Proceedings of HICSS, HICSS ’16. IEEE Computer Society, Washington, DC, pp 1072–1081
20.
Baker CF, Fillmore CJ, Lowe JB (1998) The Berkeley FrameNet project. In: Proceedings of the 17th international conference on computational linguistics—volume 1, COLING ’98. Association for Computational Linguistics, Stroudsburg, pp 86–90
21.
Navigli R, Ponzetto SP (2012) BabelNet: the automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artif Intell 193:217–250MathSciNetCrossRefMATH
22.
Kipper K, Dang HT, Palmer M (2000) Class-based construction of a verb lexicon. In: Proceedings of the seventeenth national conference on artificial intelligence and twelfth conference on innovative applications of artificial intelligence. AAAI Press/The MIT Press, Cambridge, pp 691–696
23.
Auer S, Bizer C, Kobilarov G, Lehmann J, Cyganiak R, Ives Z (2007) DBpedia: a nucleus for a web of open data. In: The semantic web: 6th ISWC 2007 + ASWC 2007, Busan, 11–15 Nov 2007, pp 722–735
24.
Suchanek FM, Kasneci G, Weikum G (2007) Yago: a core of semantic knowledge. In: Proceedings of the 16th international conference on world wide web, WWW ’07, ACM, New York, pp 697–706
25.
Lando P, Lapujade A, Kassel G, Furst F (2007) Towards a general ontology of computer programs. In: Filipe J, Shishkov B, Helfert M (eds) ICSOFT (PL/DPS/KE/MUSE), INSTICC Press, Funchal, pp 163–170
26.
Manning CD, Surdeanu M, Bauer J, Finkel JR, Bethard S, McClosky D (2014) The Stanford CoreNLP natural language processing toolkit. In: Proceedings of the 52nd ACL, Baltimore, 22–27 June 2014. System demonstrations, pp 55–60
27.
Zaharia M, Chowdhury M, Franklin MJ, Shenker S, Stoica I (2010) Spark: cluster computing with working sets. In: Proceedings of the 2Nd USENIX conference on hot topics in cloud computing, HotCloud’10. USENIX Association, Berkeley, p 10
28.
Smith TC, Frank E (2016) Statistical genomics: methods and protocols, chap. introducing machine learning concepts with WEKA. Springer, New York, pp 353–378
29.
30.
Drake A, Ringger EK, Ventura D (2008) Sentiment regression: using real-valued scores to summarize overall document sentiment. In: Proceedings of ICSC 2008, 4–7 Aug 2008, Santa Clara, pp 152–157
Metadaten
Titel
FineNews: fine-grained semantic sentiment analysis on financial microblogs and news
verfasst von
Amna Dridi
Mattia Atzeni
Diego Reforgiato Recupero
Publikationsdatum
10.03.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 8/2019
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-018-0805-x

Weitere Artikel der Ausgabe 8/2019

International Journal of Machine Learning and Cybernetics 8/2019 Zur Ausgabe

Original Article

Ensemble learning on visual and textual data for social image emotion classification

Original Article

On relational learning and discovery in social networks: a survey

Editorial

Special issue on evolutionary multi-objective optimization (EMO): theory and applications

Original Article

Topic specific emotion detection for retweet prediction

Original Article

Spam analysis of big reviews dataset using Fuzzy Ranking Evaluation Algorithm and Hadoop

Original Article

Leveraging semantics for sentiment polarity detection in social media

Neuer Inhalt

    Bildnachweise