Abstract
Analysis of blogpost writings is an important and growing research area. Both objective and subjective characteristics of a writer are detected. Words have word meaning that is common in the language and that is represented in their usage. Another component of word meaning, “personal sense”, not inherent in the language, but different for each person, reflects a meaning of words in terms of unique personal experience and carries the personal characteristics.
In our research word meaning techniques are applied to represent personal sense of words in texts by different authors. Personalized concept structures are construed and used to infer authors’ perspective from text: various notions of context combined with different thesaurus similarity scales are applied to confirm that from a certain perspective similarity in the personalized thesauri with some restrictions can correspond to similarities in the occupation of the authors.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Balahur, A., Steinberger, R.: Rethinking sentiment analysis in the news: from theory to practice and back. In: Proc. 1st Workshop on Opinion Mining and Sentiment Analysis (WOMSA), CAEPIA-TTIA Conference (2009)
Choudhury, S., Raymond, K., Higgs, P.L.: A rule-based metric for calculating semantic relatedness score for the motion picture industry. In: Workshop on Natural Language Processing and Ontology Engineering (2008)
Firth, J.R.: A synopsis of linguistic theory 1930-1955. In Studies in Linguistic Analysis. Oxford: Philological Society. Reprinted in F.R. Palmer (ed.), Selected Papers of J.R. Firth 1952-1959, London: Longman (1968)
Leontev, A.N.: Activity, Consciousness, and Personality. Prentice-Hall, Hillsdale (1978)
Mitrofanova, O., Lashevskaya, O., Panicheva, P.: Statistical Word Sense Disambiguation in Contexts for Russian Nouns Denoting Physical Objects. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds.) TSD 2008. LNCS (LNAI), vol. 5246, pp. 153–159. Springer, Heidelberg (2008)
Mohammad, S., Hirst, G.: Distributional measures of concept-distance: A task-oriented evaluation. In: Proc. EMNLP 2006 (2006)
Panicheva, P., Cardiff, J., Rosso, P.: A Co-occurrence Based Personal Sense Approach to Opinion Mining. In: Proc. 1st Workshop on Opinion Mining and Sentiment Analysis (WOMSA), CAEPIA-TTIA Conference (2009)
Panicheva, P., Cardiff, J., Rosso, P.: Personal Sense and Idiolect: Combining Authorship Attribution and Opinion Analysis. Manuscript submitted for publication (2010)
Pinto, D., Rosso, P., Juan, A., Jiménez, H.: A Comparative study of Clustering algorithms on Narrow-Domain abstracts. In: Sociedad Española para el Procesamiento del Lenguaje Natural (SEPLN) 37 (2006)
Romesburg, H.C.: Clustering Analysis for researchers. Wadsworth, Inc. (1984)
Rubenstein, H., Goodenough, J.B.: Contextual correlates of synonymy. Communications of the ACM 8(10) (1965)
Schler, J., Koppel, M., Argamon, S., Pennebaker, J.: Effects of Age and Gender on Blogging. In: Proc. 2006 AAAI Spring Symposium on Computational Approaches for Analyzing Weblogs (2006)
Wittgenstein, L.: Philosophical Investigations: The English Text of the 3rd Edition, translated by G.E.M. Anscombe. Macmillan Publishing, New York (1973)
Yoshida, S., Yukawa, T., Kuwabara, K.: Constructing and examining personalized cooccurrence-based thesauri on Web pages. In: Proc. 12th International World Wide Web Conference (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Panicheva, P., Cardiff, J., Rosso, P. (2010). Identifying Writers’ Background by Comparing Personal Sense Thesauri. In: Hopfe, C.J., Rezgui, Y., Métais, E., Preece, A., Li, H. (eds) Natural Language Processing and Information Systems. NLDB 2010. Lecture Notes in Computer Science, vol 6177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13881-2_30
Download citation
DOI: https://doi.org/10.1007/978-3-642-13881-2_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13880-5
Online ISBN: 978-3-642-13881-2
eBook Packages: Computer ScienceComputer Science (R0)