Fake news detection using machine learning
- Computer ScienceInternational journal of health sciences
This work dissect and explore different avenues regarding a bunch of clear language-autonomous elements in view of the social spread of phony news to classify them into the presented typology.
Spam Review Detection of product reviews using machine learning techniques
-----------------------------------------------------------------------------------------------------------------------------------ABSTRACT :Machine Learning is one of the fastest growing research…
Prediction of polarities of online hotel reviews: an improved stacked decision tree (ISD) approach
- BusinessGlobal Knowledge, Memory and Communication
Purpose There is a need to predict whether the consumers liked the stay in the hotel rooms or not, and to remove the aspects the customers did not like. Many customers leave a review after staying…
Creating and detecting fake reviews of online products
- Computer ScienceJournal of Retailing and Consumer Services
Detection of Fake Reviews in Social Media using Machine Learning Techniques
- Computer Science
In this proposed work, efficient techniques for detecting such fake reviews are proposed and compared, including Naive Bayes, Support Vector Machine (SVM), and K-Nearest neighbour (KNN).
A Survey on Feature Selection Based Spam Review Detection using Deep Learning Techniques
- Computer ScienceInternational Journal of Advanced Information and Communication Technology
In recent times, online shoppers are technically knowledgeable and open to product reviews. They usually read the buyer reviews and ratings before purchasing any product from ecommerce website. For…
A framework for big data analytics in commercial social networks: A case study on sentiment analysis and fake review detection for marketing decision-making
REMOTE BANKING FRAUD DETECTION FRAMEWORK USING SEQUENCE LEARNERS
- Computer Science
A conceptual fraud detection framework that can detect anomalous transaction quickly and accurately and dynamically evolve to maintain the efficiency with minimum input from subject matter expert is proposed.
Deceptive consumer review detection: a survey
- BusinessArtificial Intelligence Review
This paper unravels prominent techniques that have been proposed to solve the issue of deceptive review detection and identifies the characteristics, strengths, and bottlenecks of those methodologies which may need further improvements.
Opinion Spam Detection: A Review of the Literature
- Computer ScienceLOPAL '18
The findings of the study revealed that the approaches, which were based on machine learning and natural language processing techniques, can be classified into three categories: linguistic, behavioral and statistical.
SHOWING 1-10 OF 10 REFERENCES
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies
Review spam detection via temporal pattern discovery
- Computer ScienceKDD
It is discovered that singleton review is a significant source of spam reviews and largely affects the ratings of online stores and a hierarchical algorithm is proposed to robustly detect the time windows where such attacks are likely to have happened.
What Yelp Fake Review Filter Might Be Doing?
- Computer ScienceICWSM
This work attempts to find out what Yelp might be doing by analyzing its filtered reviews and postulates that Yelp’s filtering is reasonable and its filtering algorithm seems to be correlated with abnormal spamming behaviors.
Spotting fake reviewer groups in consumer reviews
- Computer ScienceWWW
This paper studies spam detection in the collaborative setting, i.e., to discover fake reviewer groups by using several behavioral models derived from the collusion phenomenon among fake reviewers and relation models based on the relationships among groups, individual reviewers, and products they reviewed to detectfake reviewer groups.
Detecting product review spammers using rating behaviors
- Computer ScienceCIKM
This paper identifies several characteristic behaviors of review spammers and model these behaviors so as to detect the spammers, and shows that the detected spammers have more significant impact on ratings compared with the unhelpful reviewers.
Distributional Footprints of Deceptive Product Reviews
A range of experiments confirm the hypothesized connection between the distributional anomaly and deceptive reviews and provide novel quantitative insights into the characteristics of natural distributions of opinions in the TripAdvisor hotel review and the Amazon product review domains.
Finding Deceptive Opinion Spam by Any Stretch of the Imagination
- Computer ScienceACL
This work develops and compares three approaches to detecting deceptive opinion spam, and develops a classifier that is nearly 90% accurate on the authors' gold-standard opinion spam dataset, and reveals a relationship between deceptive opinions and imaginative writing.
Support Vector Machine) http://en.wikipedia.org/wiki/Support_vector_machine  Yelp Challenge Dataset http://www.yelp.com/dataset_challenge  "Opinion Spam and Analysis
- Support Vector Machine) http://en.wikipedia.org/wiki/Support_vector_machine  Yelp Challenge Dataset http://www.yelp.com/dataset_challenge  "Opinion Spam and Analysis
- Wikipedia-n-gram http://en.wikipedia.org/wiki
- Wikipedia-Supervised Learning