Abstract
In a previous work, we developed a tool that automatically extrapolated triggers, i.e. diagnostic words for sentiments and relationships, from a manually annotated corpus, the Romanian version of the novel “Quo Vadis” by Henryk Sinkiewicz. The NodeXL program can draw graphs of character relationships, to analyse relationships both in the fictional and the real-world. In this research, we describe how we have refined our tool, which becomes both a detector and a semiautomatic (interactive, assisted) annotator of relationships in any previously morphological annotated real or fictional story. We will also show how we improved and restructured the list of triggers manually annotated in the novel “Quo Vadis”. Finally, the tool will annotate the triggers in the Chat corpus, having 2,575 sentences, part of the UAIC Romanian Dependency Treebank, a balanced corpus that contains especially non-standard Romanian language. Finally, we have made graphs to analyse the relations and sentiments of communicators from the Chat corpus.
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Hansen analyses the social media network and the relationships in Victor Hugo’s novel "Les Miserables".
References
Bradley, M.M., Lang, P.J.: Affective norms for English words (anew): instruction manual and affective ratings. In: Technical report c-1, University of Florida. The Center for Research in Psychophysiology (1999)
Colhon, M., Cristea, D., Gîfu, D.: Discovering semantic relations within nominals. In: Trandabăţ, D., Gîfu, D. (eds.) RUMOUR 2015. CCIS, vol. 588, pp. 85–100. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-32942-0_6
Colhon, M., Diac, P., Mărănduc, C., Perez, C.A.: Quo vadis research areas – text analysis. In: Proceedings of the 10th International Conference Linguistic Resources and Tools for Processing the Romanian Language. Alexandru Ioan Cuza University Publishing House, pp. 45–56 (2014)
Colhon, M., Gîfu, D., Cristea, D.: The Quo Vadis Story Telling. In: Proceedings of the the 11th International Conference Linguistic Resources and Tools for Processing The Romanian Language (ConsILR 2015). Alexandru Ioan Cuza University Publishing House, pp. 93–108 (2015)
Cristea, D., Dima, G.E., Postolache, O.D., Mitkov, R.: Handling complex anaphora resolution cases. In: Proceedings of the Discourse Anaphora and Anaphor Resolution Colloquium (DAARC 2002) (2002)
Cristea, D., et al.: Quo vadis: a corpus of entities and relations. In: Núria, G., Rapp, R., Bel-Enguix, G. (eds.) Language Production, Cognition, and the Lexicon. Springer International Publishing, pp. 505– 543 (2015)
Cristea, D., Ignat, E.: Linking book characters. toward a corpus encoding relations between entities. In: Proceedings of the 7th International Conference on Speech Technology and Human-Computer Dialogue (SpeD 2013), pp. 1–8 (2013)
Ekman, P.: An argument for basic emotions. Cognition and Emotion 6 (1992)
Esuli, A., Sebastiani, F.: Sentiwordnet: a publicly available lexical resource for opinion mining. In: Proceedings of the 5th Conference on Language Resources and Evaluation (LREC 2006), pp. 417–422 (2006)
Farzindar, A., Inkpen, D.: Natural Language Processing for Social Media. Morgan & Claypool Publishers (2015)
Hansen, D.L., Shneiderman, B., Smith, M.A.: Analyzing Social Media Networks with NodeXL. Morgan Kaufmann (2011)
Hearst, M.A.: Automatic acquisition of hyponyms from large text corpora. – Association for Computational Linguistics, vol. 2, pp. 539–545 (1992)
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computational Linguistics, pp. 168–77 (2004)
Malandrakis, N., Potamianos, A., Iosif, E., Narayanan, S.: Distributional semantic models for affective text analysis. IEEE Trans. Audio, Speech Lang. Process. 21(11), 2379–2392 (2007)
Pang, B., Lee, L.: Opinion mining and sentiment analysis. Found. Trends Inf. Retrieval (2008)
Perez, C.A., Mărănduc, C., Simionescu, R.: Including social media – a very dynamic style – in the corpora for processing Romanian language. In: Linguistic Linked Open Data: 12th EUROLAN 2015 Summer School and RUMOUR 2015 Workshop, Sibiu, Romania, 13–25 July 2015, Revised Selected Papers, pp. 139–153 (2016a)
Perez, C.A., Mărănduc, C., Simionescu, R.: Social media – processing Romanian chats and discourse analysis. Computación y Sistemas 20(3), 404–414 (2016b). https://doi.org/10.13053/CyS-20-3-2453
Poria, S., Agarwal, B., Gelbukh, A., Hussain, A., Howard, N.: Dependency-based semantic parsing for concept level text analysis. Comput. Linguistics Intell. Text Process. CICLing 2014 (2014)
Valitutti, R.: Wordnet-affect: an affective extension of wordnet. In: Proceedings of the 4th International Conference on Language Resources and Evaluation, pp. 1083–1086 (2004)
Wiebe, J., Mihalcea, R.: Word sense and subjectivity. In: Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics. Association for Computational Linguistics, pp. 1065–1072 (2006)
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Diac, P., Mărănduc, C., Colhon, M. (2023). Relationships and Sentiment Analysis of Fictional or Real Characters. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2018. Lecture Notes in Computer Science, vol 13397. Springer, Cham. https://doi.org/10.1007/978-3-031-23804-8_8
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