The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Detection of review spam: A survey
Overview
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Citations
Cites
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
Sentiment Analysis and Opinion Mining
Liu, B. (2012) · Synthesis Lectures on Human Language Technologies · doi:10.1007/978-3-031-02145-9 · Cited by 3,281
Sentiment Analysis and Opinion Mining
Zhang, L., & Liu, B. (2017) · Encyclopedia of Machine Learning and Data Mining · doi:10.1007/978-1-4899-7687-1_907 · Cited by 3,260
Zhu, F., & Zhang, X. (. (2010) · Journal of Marketing · doi:10.1509/jm.74.2.133 · Cited by 2,363
Extracting product features and opinions from reviews
Popescu, A.-M., & Etzioni, O. (2005) · Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing - HLT '05 · doi:10.3115/1220575.1220618 · Cited by 1,698
On the resemblance and containment of documents
Broder, A. Z. (2002) · Proceedings. Compression and Complexity of SEQUENCES 1997 (Cat. No.97TB100171) · doi:10.1109/sequen.1997.666900 · Cited by 1,698
The Development and Psychometric Properties of LIWC2015
Pennebaker, J. W., Boyd, R. L., Jordan, K., & Blackburn, K. (2015) · University of Texas at Austin · doi:10.15781/t25p41 · Cited by 1,674
Jindal, N., & Liu, B. (2008) · Proceedings of the international conference on Web search and web data mining - WSDM '08 · doi:10.1145/1341531.1341560 · Cited by 1,542
Finding Deceptive Opinion Spam by Any Stretch of the Imagination
Ott, M., Choi, Y., Cardie, C., & Hancock, J. T. (2011) · arXiv · doi:10.48550/arxiv.1107.4557 · Cited by 1,008
Cited by
A survey on opinion mining and sentiment analysis: Tasks, approaches and applications
Ravi, K., & Ravi, V. (2015) · Knowledge-Based Systems · doi:10.1016/j.knosys.2015.06.015 · Cited by 1,306
Fake online reviews: Literature review, synthesis, and directions for future research
Wu, Y., Ngai, E. W. T., Wu, P., & Wu, C. (2020) · Decision Support Systems · doi:10.1016/j.dss.2020.113280 · Cited by 359
Credibility in social media: opinions, news, and health information—a survey
Viviani, M., & Pasi, G. (2017) · WIREs Data Mining and Knowledge Discovery · doi:10.1002/widm.1209 · Cited by 221
Hajek, P., Barushka, A., & Munk, M. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-04757-2 · Cited by 186
Detection of malicious social bots: A survey and a refined taxonomy
Latah, M. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.113383 · Cited by 94
Metadata
- Authors
- Heydari, A., Tavakoli, M. A., Salim, N., & Heydari, Z.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2015-05
- Volume
- 42
- Issue
- 7
- Pages
- 3634-3642
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W1977764012
- Cited by
- 290
- References
- 48
- FWCI
- 50.85
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
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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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Detection of review spam: A survey. https://app.cochat.ai/papers/10.1016/j.eswa.2014.12.029
- The paper
- Heydari, A., Tavakoli, M. A., Salim, N., & Heydari, Z. (2015). Detection of review spam: A survey. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2014.12.029
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
