Academic plagiarism detection: a systematic literature review

T Foltýnek, N Meuschke, B Gipp - ACM Computing Surveys (CSUR), 2019‏ - dl.acm.org
This article summarizes the research on computational methods to detect academic
plagiarism by systematically reviewing 239 research papers published between 2013 and …

Multi-feature, multi-modal, and multi-source social event detection: A comprehensive survey

I Afyouni, Z Al Aghbari, RA Razack - Information Fusion, 2022‏ - Elsevier
The tremendous growth of event dissemination over social networks makes it very
challenging to accurately discover and track exciting events, as well as their evolution and …

Arabic text classification using deep learning models

A Elnagar, R Al-Debsi, O Einea - Information Processing & Management, 2020‏ - Elsevier
Text classification or categorization is the process of automatically tagging a textual
document with most relevant labels or categories. When the number of labels is restricted to …

From citizens to government policy-makers: Social media data analysis

OB Driss, S Mellouli, Z Trabelsi - Government Information Quarterly, 2019‏ - Elsevier
People are more and more using social media to express themselves about the different
services that their governments are delivering. They can either provide positive or negative …

Attention-based long short-term memory network using sentiment lexicon embedding for aspect-level sentiment analysis in Korean

M Song, H Park, K Shin - Information Processing & Management, 2019‏ - Elsevier
Although deep learning breakthroughs in NLP are based on learning distributed word
representations by neural language models, these methods suffer from a classic drawback …

Does the review deserve more helpfulness when its title resembles the content? Locating helpful reviews by text mining

S Yang, J Yao, A Qazi - Information Processing & Management, 2020‏ - Elsevier
Online review helpfulness has always sparked a heated discussion among academics and
practitioners. Despite the fact that research has extensively examined the impacts of review …

Short-text semantic similarity (stss): Techniques, challenges and future perspectives

ZH Amur, Y Kwang Hooi, H Bhanbhro, K Dahri… - Applied Sciences, 2023‏ - mdpi.com
In natural language processing, short-text semantic similarity (STSS) is a very prominent
field. It has a significant impact on a broad range of applications, such as question …

A deep network model for paraphrase detection in short text messages

B Agarwal, H Ramampiaro, H Langseth… - Information Processing & …, 2018‏ - Elsevier
This paper is concerned with paraphrase detection, ie, identifying sentences that are
semantically identical. The ability to detect similar sentences written in natural language is …

Paraphrase identification with deep learning: A review of datasets and methods

C Zhou, C Qiu, L Liang, DE Acuna - arxiv preprint arxiv:2212.06933, 2022‏ - arxiv.org
The rapid progress of Natural Language Processing (NLP) technologies has led to the
widespread availability and effectiveness of text generation tools such as ChatGPT and …

Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media

Y Albalawi, J Buckley, NS Nikolov - Journal of big Data, 2021‏ - Springer
This paper presents a comprehensive evaluation of data pre-processing and word
embedding techniques in the context of Arabic document classification in the domain of …