![](bg9.png)
ysis of results across sectors, and across companies
within sectors, should yield insights that could inform
a more sophisticated processing architecture, as well
as a more effective document representation.
REFERENCES
Bar-Haim, R., Dinur, E., Feldman, R., Fresko, M., and
Goldstein, G. (2011). Identifying and following ex-
pert investors in stock microblogs. In Proceedings of
the 2011 Conference on Empirical Methods in Natural
Language Processing, pages 1310–1319, Edinburgh,
Scotland, UK.
Bulyko, I. and Ostendorf, M. (2003). Getting more mileage
from web text sources for conversational speech lan-
guage modeling using class-dependent mixtures. In
Proc. HLT-NAACL 2003, pages 7–9.
Chua, C., Milosavljevic, M., and Curran, J. R. (2009). A
sentiment detection engine for internet stock message
boards. In Proceedings of the Australasian Language
Technology Association Workshop 2009, pages 89–93,
Sydney, Australia.
Das, D. and Smith, N. A. (2011). Semi-supervised frame-
semantic parsing for unknown predicates. In Proceed-
ings of the 49th Annual Meeting of the ACL, HLT ’11,
pages 1435–1444, Stroudsburg, PA, USA.
Das, D. and Smith, N. A. (2012). Graph-based lexicon
expansion with sparsity-inducing penalties. In HLT-
NAACL, pages 677–687.
Devitt, A. and Ahmad, K. (2007). Sentiment polarity iden-
tification in financial news: A cohesion-based ap-
proach. In Proceedings of the 45th Annual Meeting
of the ACL, pages 984–991, Prague, Czech Republic.
Engelberg, J. and Parsons, C. A. (2011). The causal impact
of media in financial markets. Journal of Finance,
66(1):67–97.
Feldman, R., Rosenfeld, B., Bar-Haim, R., and Fresko,
M. (2011). The stock sonar - sentiment analysis of
stocks based on a hybrid approach. In Proceedings of
the Twenty-Third Conference on Innovative Applica-
tions of Artificial Intelligence, August 9-11, 2011, San
Francisco, California, USA.
Fillmore, C. J. (1976). Frame semantics and the nature of
language. Annals of the New York Academy of Sci-
ences, 280(1):20–32.
Gentzkow, M. and Shapiro, J. M. (2010). What drives media
slant? Evidence from U.S. daily newspapers. Econo-
metrica, 78(1):3571.
Haider, S. A. and Mehrotra, R. (2011). Corporate news
classification and valence prediction: A supervised
approach. In Proceedings of the 2nd Workshop on
Computational Approaches to Subjectivity and Senti-
ment Analysis (WASSA 2.011), pages 175–181, Port-
land, Oregon.
Kogan, S., Levin, D., Routledge, B. R., Sagi, J. S., and
Smith, N. A. (2009). Predicting risk from financial re-
ports with regression. In Proceedings of Human Lan-
guage Technologies: The 2009 Annual Conference of
the North American Chapter of the ACL, NAACL ’09,
pages 272–280, Stroudsburg, PA, USA.
Lee, H., Chang, A., Peirsman, Y., Chambers, N., Surdeanu,
M., and Jurafsky, D. (2013). Deterministic coref-
erence resolution based on entity-centric, precision-
ranked rules. Computational Linguistics, 39(4).
Luss, R. and d’Aspremont, A. (2008). Predicting abnor-
mal returns from news using text classification. CoRR,
abs/0809.2792.
Manning, C. D., Surdeanu, M., Bauer, J., Finkel, J.,
Bethard, S. J., and McClosky, D. (2014). The Stanford
CoreNLP natural language processing toolkit. In Pro-
ceedings of 52nd Annual Meeting of the ACL, pages
55–60.
McClosky, D., Charniak, E., and Johnson, M. (2010). Auto-
matic domain adaptation for parsing. In Human Lan-
guage Technologies: The 2010 Annual Conference of
the North American Chapter of the ACL, HLT ’10,
pages 28–36, Stroudsburg, PA, USA.
Moschitti, A. (2006). Making tree kernels practical for nat-
ural language learning. In In Proceedings of the 11th
Conference of the European Chapter of the ACL.
O’Connor, B., Stewart, B. M., and Smith, N. A. (2013).
Learning to extract international relations from politi-
cal context. In Proceedings of the 51st Annual Meet-
ing of the ACL, pages 1094–1104, Sofia, Bulgaria.
Ravi, S., Knight, K., and Soricut, R. (2008). Automatic pre-
diction of parser accuracy. In Proceedings of the 2008
Conference on Empirical Methods in Natural Lan-
guage Processing, pages 887–896, Honolulu, Hawaii.
Rosenfeld, B. and Feldman, R. (2007). Using corpus statis-
tics on entities to improve semi-supervised relation
extraction from the web. In ACL 2007, Proceedings
of the 45th Annual Meeting of the ACL, June 23-30,
2007, Prague, Czech Republic.
Roux, J. L., Foster, J., Wagner, J., Samad, R., Kaljahi, Z.,
and Bryl, A. (2012). DUC-Paris13 systems for the
SANCL 2012 shared task.
Sarikaya, R., Gravano, A., and Gao, Y. (2005). Rapid
language model development using external resources
for new spoken dialog domains. In International
Congress of Acoustics, Speech, and Signal Processing
(ICASSP), pages 573–576, Philadelphia, PA, USA.
IEEE, Signal Processing Society.
Tetlock, P. C. (2007). Giving Content to Investor Sentiment:
The Role of Media in the Stock Market. The Journal
of Finance.
Whissel, C. M. (1989). The dictionary of affect in lan-
guage. Emotion: Theory, Research, and Experience,
39(4):113–131.
Wolodja Wentland, Johannes Knopp, C. S. and Hartung, M.
(2008). Building a multilingual lexical resource for
named entity disambiguation, translation and translit-
eration. In (ELRA), E. L. R. A., editor, Proceedings of
the Sixth International Language Resources and Eval-
uation (LREC’08), Marrakech, Morocco.
Xie, B., Passonneau, R. J., Wu, L., and Creamer, G. (2013).
Semantic frames to predict stock price movement. In
Proceedings of the 51st Annual Meeting of the ACL,
pages 873–883, Sofia, Bulgaria.
KDIR2014-InternationalConferenceonKnowledgeDiscoveryandInformationRetrieval
520