Results 31 to 40 of about 346,740 (322)

Fake Review Detection Using Machine Learning

Journal of Student Research, 2022
E-commerce and online shopping is a booming industry, especially during the COVID-19 pandemic. Online shopping allows customers to browse and purchase products from home using just a phone or laptop. Customers often never end up seeing their product in real life before the purchase, and are instead dependent on photos and descriptions uploaded by the ...
Aaryan Rustagi, Vajraang Padisetti, Suresh Subramaniam   +2 more
openaire   +1 more source

Fake Reviewer Group Detection in Online Review Systems [PDF]

2021 International Conference on Data Mining Workshops (ICDMW), 2021
Online review systems are important components in influencing customers' purchase decisions. To manipulate a product's reputation, many stores hire large numbers of people to produce fake reviews to mislead customers. Previous methods tackle this problem by detecting malicious individuals, ignoring the fact that the spam activities are often formed in ...
Cao, Chen, Li, Shihao, Yu, Shuo, Chen, Zhikui   +3 more
openaire   +2 more sources

BSTC: A Fake Review Detection Model Based on a Pre-Trained Language Model and Convolutional Neural Network

Electronics, 2023
Detecting fake reviews can help customers make better purchasing decisions and maintain a positive online business environment. In recent years, pre-trained language models have significantly improved the performance of natural language processing tasks.
Junwen Lu, Xintao Zhan, Guanfeng Liu, Xinrong Zhan, Xiaolong Deng   +4 more
semanticscholar   +1 more source

Fake news detection: state-of-the-art review and advances with attention to Arabic language aspects [PDF]

PeerJ Computer Science
The proliferation of fake news has become a significant threat, influencing individuals, institutions, and societies at large. This issue has been exacerbated by the pervasive integration of social media into daily life, directly shaping opinions, trends,
Eman Salamah Albtoush, Keng Hoon Gan, Saif A. Ahmad Alrababa   +2 more
doaj   +2 more sources

Task-specific Word Identification from Short Texts Using a Convolutional Neural Network

, 2017
Task-specific word identification aims to choose the task-related words that best describe a short text. Existing approaches require well-defined seed words or lexical dictionaries (e.g., WordNet), which are often unavailable for many applications such ...
Wu, Xintao, Xiang, Yang, Yuan, Shuhan
core   +1 more source

Coincidence analysis to search for inspiraling compact binaries using TAMA300 and LISM data [PDF]

, 2003
Japanese laser interferometric gravitational wave detectors, TAMA300 and LISM, performed a coincident observation during 2001. We perform a coincidence analysis to search for inspiraling compact binaries.
Akira Okutomi, Akira Yamamoto, Akiteru Takamori, Akito Araya, Akitoshi Ueda, B. Abbott, B. Abbott, B. Allen, C. Cutler, Colin T. Taylor, D. Nicholson, Daisuke Tatsumi, E. Amaldi, Fumihiko Usui, Gen’ichi Horikoshi, Gerhard Heinzel, H. Tagoshi, Hideki Asada, Hideki Ishitsuka, Hidetsugu Seki, Hideyuki Tagoshi, Hiromi Yakura, Hirotaka Takahashi, Hiroyuki Nakano, Kazuaki Kuroda, Kazuhiro Hayama, Kazuhiro Kondo, Kazuhiro Yamamoto, Kazuyuki Miura, Keita Kawabe, Ken-ichi Nakao, Ken-ichi Oohara, Ken-ichi Ueda, Kenji Numata, Kenji Soida, Kentaro Somiya, Ken’ichi Nakagawa, Kimio Tsubono, Kohei Takeno, Koichi Waseda, Koji Arai, Kuniharu Tochikubo, Kunihiko Kasahara, Kunihito Ioka, L. Blanchet, L. Blanchet, L. Blanchet, M. Ando, Mark A. Barton, Masa-Katsu Fujimoto, Masaki Ando, Masaru Shibata, Masatake Ohashi, Misao Sasaki, Mitsuhiro Fukushima, Mitsuru Musha, Namio Matsuda, Naoki Seto, Naoko Ohishi, Nobuaki Sato, Nobuhiro Tsuda, Nobuki Kawashima, Nobuyuki Kanda, Norihiko Kamikubota, Norikatsu Mio, Osamu Miyakawa, P. Astone, P. Astone, Peter Beyersdorf, Ryutaro Takahashi, S. Droz, S. Sato, S. Sato, S.J. Curran, Seiji Kawamura, Shigemi Otsuka, Shigenori Moriwaki, Shigeo Nagano, Shinji Miyoki, Shinsuke Taniguchi, Shoken Miyama, Shuichi Sato, Shuzo Takemoto, Souichi Telada, T. Tanaka, Takahiro Tanaka, Takakazu Shintomi, Takashi Nakamura, Takashi Uchiyama, Takayuki Tomaru, Tatsuo Yoda, Tomiyoshi Haruyama, Toru Tanji, Toshifumi Futamase, Toshikazu Suzuki, Toshitaka Yamazaki, Yasufumi Kojima, Yoji Totsuka, Yoshihide Kozai, Yoshiki Tsunesada, Yoshio Saito, Youich Aso, Yuhiko Nishi, Yujiro Ogawa, Yukiyoshi Iida, Yuko Watanabe, Zong-Hong Zhu   +106 more
core   +2 more sources

Munchausen by internet: current research and future directions. [PDF]

, 2012
The Internet has revolutionized the health world, enabling self-diagnosis and online support to take place irrespective of time or location. Alongside the positive aspects for an individual's health from making use of the Internet, debate has intensified
Alinejad, NA, Andy Pulman, Asher, R, Barak, A, Berners-Lee, T, Boehm, FH, Doescher, MP, Doherty, AM, Donath, JS, Eysenbach, G, Feldman, MD, Field, MG, Gavin, H, Jacqui Taylor, Joinson, A, Lipsitt, DR, Lurid, FB, Madden, M, Meadow, R, Mealy, M, Oltmanns, FT, Pearson, SD, Pulman, A, Recupero, PR, Resnick, PJ, Savino, AC, Shea, V, Sherman, M, Turkle, S   +28 more
core   +2 more sources

Fake Online Reviews: A Unified Detection Model Using Deception Theories

IEEE Access, 2022
Online reviews influence consumers’ purchasing decisions. However, identifying fake online reviews automatically remains a complex problem, and current detection approaches are inefficient in preventing the spread of fake reviews.
Mujahed Abdulqader, Abdallah Namoun, Yazed Alsaawy   +2 more
doaj   +1 more source

Detecting Singleton Review Spammers Using Semantic Similarity

, 2016
Online reviews have increasingly become a very important resource for consumers when making purchases. Though it is becoming more and more difficult for people to make well-informed buying decisions without being deceived by fake reviews.
Blei D. M., Fei G., Feng S., Mihalcea R., Moghaddam S. A., Mukherjee A., Ott M., Sandulescu V., Zengin M.   +8 more
core   +1 more source

A Survey on the Use of Large Language Models (LLMs) in Fake News

Future Internet
The proliferation of fake news and fake profiles on social media platforms poses significant threats to information integrity and societal trust. Traditional detection methods, including rule-based approaches, metadata analysis, and human fact-checking ...
Eleftheria Papageorgiou, Christos Chronis, Iraklis Varlamis, Yassine Himeur   +3 more
doaj   +1 more source