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Detecting Vietnamese Opinion Spam

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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T.H.H Duong, T.D. Vu, V.M. Ngo

Information Retrieval · Submitted 9 May 2019

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim The accuracy of our method is up to 90%.

how it is stated · asserted 1.00 read the record →

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arXiv ID1905.06112 (version 1)
Pith IDU6HNGOKM, Pith's permanent record of this paper and its review
CitationT.D. Vu, T.H.H Duong, V.M. Ngo. "Detecting Vietnamese Opinion Spam." arXiv:1905.06112 (2019). https://pith.science/paper/U6HNGOKM
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 5,964 input tokens.

What the abstract itself states, as probabilities: claims first 0.17 · states limitation 0.08 · human participants 0.08 · controlled comparison 0.04 · randomized assignment 0.01 · states quantitative result 0.98 · compares with prior results 0.07 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

Recently, Vietnamese Natural Language Processing has been researched by experts in academic and business. However, the existing papers have been focused only on information classification or extraction from documents. Nowadays, with quickly development of the e-commerce websites, forums and social networks, the products, people, organizations or wonders are targeted of comments or reviews of the network communities. Many people often use that reviews to make their decision on something. Whereas, there are many people or organizations use the reviews to mislead readers. Therefore, it is so necessary to detect those bad behaviors in reviews. In this paper, we research this problem and propose an appropriate method for detecting Vietnamese reviews being spam or non-spam. The accuracy of our method is up to 90%.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 Recently, Vietnamese Natural Language Processing has been researched by experts in academic and business. background 1.00 0.04 0.01 asserted 1.00
s1 However, the existing papers have been focused only on information classification or extraction from documents. gap 0.99 0.05 0.02 asserted 1.00
s2 Nowadays, with quickly development of the e-commerce websites, forums and social networks, the products, people, organizations or wonders are targeted of comments or reviews of the network communities. background 1.00 0.04 0.02 asserted 0.99
s3 Many people often use that reviews to make their decision on something. background 1.00 0.04 0.02 asserted 1.00
s4 Whereas, there are many people or organizations use the reviews to mislead readers. background 0.96 0.04 0.02 asserted 1.00
s5 Therefore, it is so necessary to detect those bad behaviors in reviews. background 0.67 0.05 0.08 asserted 1.00
s6 In this paper, we research this problem and propose an appropriate method for detecting Vietnamese reviews being spam or non-spam. contribution 1.00 0.90 0.21 asserted 0.99
s7 The accuracy of our method is up to 90%. result 1.00 0.95 0.60 asserted 1.00

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from observation or experiment 0.80.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

Recently, Vietnamese Natural Language Processing has been researched by experts in academic and business. However, the existing papers have been focused only on information classification or extraction from documents. Nowadays, with quickly development of the e-commerce websites, forums and social networks, the products, people, organizations or wonders are targeted of comments or reviews of the network communities. Many people often use that reviews to make their decision on something. Whereas, there are many people or organizations use the reviews to mislead readers. Therefore, it is so necessary to detect those bad behaviors in reviews. In this paper, we research this problem and propose an appropriate method for detecting Vietnamese reviews being spam or non-spam. The accuracy of our method is up to 90%.

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