A random walk algorithm for automatic construction of domain-oriented sentiment lexicon
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Most datasets used in the tourism sentiment analysis literature relate to hotel accommodation.
“It is also noted that most of the datasets used in the literature relate to hotel accommodation (e.g., Kasper &Vela, 2011 and2012;Tan & Wu, 2011;Bjorkelund et al., 2012;Gräbner et al., 2012;Bucur 2015;Marrese-Taylora et al., 2013;Markopoulos et al., 2015;Rossetti et al., 2015).”
From Sentiment Analysis in Tourism: Capitalizing on Big Data (2019) · cites this paper as Tan & Wu, 2011
Most studies have used data written in English for sentiment analysis, but few used reviews written in Chinese, Spanish and German.
“Most studies have used data written in English for sentiment analysis, but few used reviews written in Chinese, Spanish and German (Zheng & Ye, 2009;Tan & Wu, 2011;Garcia et al, 2012;Kasper & Vela, 2011;Zhang et al., 2011).”
From Sentiment Analysis in Tourism: Capitalizing on Big Data (2019) · cites this paper as Tan & Wu, 2011
Cites
(1999) · Cited by 12,854 · see citing works
Mining and summarizing customer reviews
Hu, M., & Liu, B. (2004) · Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1014052.1014073 · Cited by 7,793 · see citing works
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
Peter, P., & Turney (2002) · Cited by 3,646 · see citing works
LexRank: Graph-based Lexical Centrality as Salience in Text Summarization
Erkan, G., & Radev, D. R. (2004) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1523 · Cited by 2,975 · see citing works
Turney, P. D. (2001) · Annual Meeting of the Association for Computational Linguistics (ACL) · doi:10.3115/1073083.1073153 · Cited by 2,354 · see citing works
Authoritative sources in a hyperlinked environment
Kleinberg, J. M. (1998) · Symposium on Discrete Algorithms · doi:10.5555/314613.315045 · Cited by 1,815 · see citing works
Extracting product features and opinions from reviews
Popescu, A.-M., & Etzioni, O. (2005) · doi:10.3115/1220575.1220618 · Cited by 1,714 · see citing works
Measuring praise and criticism
Turney, P. D., & Littman, M. L. (2003) · ACM Transactions on Information Systems · doi:10.1145/944012.944013 · Cited by 1,515 · see citing works
Determining the sentiment of opinions
Kim, S.-M., & Hovy, E. H. (2004) · International Conference on Computational Linguistics · doi:10.3115/1220355.1220555 · Cited by 1,499 · see citing works
Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL
Turney, P. D. (2001) · Lecture notes in computer science · doi:10.1007/3-540-44795-4_42 · Cited by 1,305 · see citing works
Predicting the semantic orientation of adjectives
Hatzivassiloglou, V., & McKeown, K. R. (1997) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.3115/979617.979640 · Cited by 822 · see citing works
Using WordNet to Measure Semantic Orientations of Adjectives
Kamps, J., Marx, M., Mokken, R. J., & de Rijke, M. (2004) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/222z3zcs9izx · Cited by 654 · see citing works
Opinion Extraction, Summarization and Tracking in News and Blog Corpora.
Ku, L., Liang, Y., & Chen, H. (2006) · Cited by 479 · see citing works
A survey on sentiment detection of reviews
Tang, H., Tan, S., & Cheng, X. (2009) · Expert Systems with Applications · doi:10.1016/j.eswa.2009.02.063 · Cited by 477 · see citing works
Self-citationAn empirical study of sentiment analysis for chinese documents
TAN, S., & ZHANG, J. (2007) · Expert Systems with Applications · doi:10.1016/j.eswa.2007.05.028 · Cited by 437 · see citing works
Self-citationFully automatic lexicon expansion for domain-oriented sentiment analysis
Kanayama, H., & Nasukawa, T. (2006) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/1610075.1610125 · Cited by 414 · see citing works
Determining the semantic orientation of terms through gloss classification
Esuli, A., & Sebastiani, F. (2005) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/1099554.1099713 · Cited by 390 · see citing works
LexRank: Graph-based Centrality as Salience in Text Summarization
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Adapting Naive Bayes to Domain Adaptation for Sentiment Analysis
Tan, S., Cheng, X., Wang, Y., & Xu, H. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-00958-7_31 · Cited by 193 · see citing works
Self-citationWan, X., & Xiao, J. (2008) · International Conference on Computational Linguistics · doi:10.3115/1599081.1599203 · Cited by 146 · see citing works
A novel scheme for domain-transfer problem in the context of sentiment analysis
Tan, S., Wu, G., Tang, H., & Cheng, X. (2007) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/1321440.1321590 · Cited by 113 · see citing works
Self-citationAutomatic identification of sentiment vocabulary
Gamon, M., & Aue, A. (2005) · doi:10.3115/1610230.1610241 · Cited by 99 · see citing works
Du, W., Tan, S., Cheng, X., & Yun, X. (2010) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/1718487.1718502 · Cited by 93 · see citing works
Self-citationSentiRank: Cross-Domain Graph Ranking for Sentiment Classification
Wu, Q., Tan, S., Zhai, H., Zhang, G., Duan, M., & Cheng, X. (2009) · IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) · doi:10.1109/wi-iat.2009.55 · Cited by 14 · see citing works
Self-citation
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Medhat, W., Hassan, A., & Korashy, H. (2014) · Ain Shams Engineering Journal · doi:10.1016/j.asej.2014.04.011 · Cited by 3,265 · see citing works
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Alaei, A. R., Becken, S., & Stantic, B. (2019) · Journal of Travel Research · doi:10.1177/0047287517747753 · Cited by 622 · see citing works
Analytical mapping of opinion mining and sentiment analysis research during 2000–2015
Piryani, R., Madhavi, D., & Singh, V. K. (2016) · Information Processing & Management · doi:10.1016/j.ipm.2016.07.001 · Cited by 205 · see citing works
Unsupervised method for sentiment analysis in online texts
Fernández‐Gavilanes, M., Álvarez-López, T., Juncal-Martínez, J., Costa‐Montenegro, E., & González-Castaño, F. J. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.03.031 · Cited by 161 · see citing works
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Moreo, A., Romero, M., Castro, J. L., & Zurita, J. M. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.02.057 · Cited by 146 · see citing works
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Puh, K., & Babac, M. B. (2022) · Journal of Hospitality and Tourism Insights · doi:10.1108/jhti-02-2022-0078 · Cited by 145 · see citing works
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Feng, X., Wei, Y., Pan, X., Qiu, L., & Ma, Y. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17061941 · Cited by 53 · see citing works
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Automatic construction of target-specific sentiment lexicon
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Beigi, O. M., & Moattar, M. H. (2020) · Knowledge-Based Systems · doi:10.1016/j.knosys.2020.106423 · Cited by 46 · see citing works
Corpus-Based Techniques for Sentiment Lexicon Generation: A Review
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Review on sentiment analysis for text classification techniques from 2010 to 2021
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Zhang, J., & Peng, Q. (2012) · IEEE International Conference on Information and Automation (ICIA) · doi:10.1109/icinfa.2012.6246900 · Cited by 6 · see citing works
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A new approach for a domain-independent turkish sentiment seed lexicon compilation.
Ekıncı, E., & Omurca, S. İ. (2019) · The International Arab Journal of Information Technology · Cited by 4 · see citing works
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Naik, M. V., Ansari, M. D., Gunjan, V. K., & Kumar, S. (2020) · Lecture notes in electrical engineering · doi:10.1007/978-981-15-3125-5_35 · Cited by 4 · see citing works
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Naik, M. V., Vasumathi, D., & Kumar, A. P. S. (2020) · International Journal of Sensors Wireless Communications and Control · doi:10.2174/2210327910999200528114552 · Cited by 2 · see citing works
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R, B. G., Santhi, B., & Swaminatha, P. (2014) · Journal of Applied Sciences · doi:10.3923/jas.2014.1633.1637 · Cited by 1 · see citing works
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Rojas-Hernández, R., López‐Chau, A., Valle-Cruz, D., Mora, V. T., & Jaimes, E. I. G. (2023) · IEEE Symposium Series on Computational Intelligence (SSCI) · doi:10.1109/ssci52147.2023.10371996 · Cited by 1 · see citing works
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Haardt, V., Malandri, L., Mercorio, F., & Porcelli, L. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-74633-8_28 · Cited by 1 · see citing works
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Alqaryouti, O. (2017) · Cited by 1 · see citing works
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Nijin, V., Ra, K., Swathika, R., & Mohanavalli, S. (2013) · doi:10.5121/csit.2013.3505
Alshahrani, H. A. (2018) · ScholarWorks - WMU (Western Michigan University)
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Wang, Y., Qiao, P., Sun, G., Fan, K., & Zeng, X. (2019) · Revue d intelligence artificielle · doi:10.18280/ria.330202
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- Authors
- Tan, S., & Wu, Q.
- Affiliations
- Chinese Academy of Sciences (CN)
- Corresponding author
- Tan, Songbo
- ORCID
- Wu, Qiong
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2011-09
- Volume
- 38
- Issue
- 10
- Pages
- 12094-12100
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2028998631
- Cited by
- 55
- References
- 24
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 3 · 2022: 4 · 2021: 7 · 2020: 8 · 2019: 5 · 2018: 6 · 2017: 3 · 2016: 2 · 2015: 5 · 2014: 2 · 2013: 3 · 2012: 3
- FWCI
- 2.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Expert Systems with Applications (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- sentiment lexicon construction, random walk algorithm, sentiment words, graph learning
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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