Product feature sentiment analysis based on GRU-CAP considering Chinese sarcasm recognition

Review Engineering, Industrial

Explainable neural network-based approach to Kano categorisation of product features from online reviews

Junegak Joung et al.

Summary: The paper introduces a neural network-based approach to classify product features into Kano categories using online reviews, demonstrating higher reliability and efficiency in Kano analysis.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH (2022)

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Article Computer Science, Artificial Intelligence

A spatiotemporal multi-feature extraction framework for opinion mining

Tiankuo Li et al.

Summary: With the rapid development of Internet technology and the explosive growth of digital text, opinion mining has become an important research hotspot in the field of natural language processing (NLP). This paper proposes a new deep learning framework for opinion mining, which is shown to outperform other algorithms in terms of performance.

NEUROCOMPUTING (2022)

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Article Computer Science, Artificial Intelligence

Multi-label emotion classification of Urdu tweets

Noman Ashraf et al.

Summary: This study created the first multi-label emotion dataset in Urdu and adopted a multi-label classification approach for emotion detection. Due to the morphological and syntactic structure of Urdu, emotion detection posed a challenging problem. The study experimented with various baseline classifiers and different text representation methods, and presented the best results obtained.

PEERJ COMPUTER SCIENCE (2022)

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Proceedings Paper Computer Science, Information Systems

Masking and Generation: An Unsupervised Method for Sarcasm Detection

Rui Wang et al.

Summary: Existing approaches for sarcasm detection rely heavily on labeled data or extra information, which is costly and often unavailable in low-resource conditions. In this study, we propose an unsupervised perspective for sarcasm detection, using a masking and generation paradigm to extract context incongruities and improve sentence representation through unsupervised contrastive learning. Experimental results demonstrate that our approach outperforms baselines and achieves comparable performance with supervised methods on sarcasm datasets.

PROCEEDINGS OF THE 45TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR '22) (2022)

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Article Computer Science, Artificial Intelligence

CFN: A Complex-Valued Fuzzy Network for Sarcasm Detection in Conversations

Yazhou Zhang et al.

Summary: Sarcasm detection in conversation is a challenging artificial intelligence task that aims to discover ironically, contemptuously, and metaphorically implied information in daily conversations. A complex-valued fuzzy network leveraging quantum theory and fuzzy logic is proposed to address the intrinsic vagueness and uncertainty of human language in emotional expression and understanding, outperforming strong baselines in extensive experiments.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2021)

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Article Engineering, Mechanical

Automated Keyword Filtering in Latent Dirichlet Allocation for Identifying Product Attributes From Online Reviews

Junegak Joung et al.

Summary: Identifying product attributes from the perspective of customers is essential in product design. This article proposes an automated method for identifying product attributes and validates its effectiveness through a case study of Android smartphones.

JOURNAL OF MECHANICAL DESIGN (2021)

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Article Business

The role of visual cues in eWOM on consumers' behavioral intention and decisions

Raffaele Filieri et al.

Summary: This study investigates how different visual and verbal eWOM cues influence tourists' intention and decision to visit tourist destinations, finding that eWOM mainly affects tourists' intentions and decisions through visual cues, rather than information quality.

JOURNAL OF BUSINESS RESEARCH (2021)

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Proceedings Paper Automation & Control Systems

A fuzzy approach for sarcasm detection in social networks

Amina Ben Meriem et al.

Summary: The great success of social networks is attributed to providing users a space of free expression where they can generate a large amount of information, posing challenges for data analysts. The ease of use of social media encourages users to express their opinions more, and sarcasm detection is a subarea of sentiment analysis.

KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KSE 2021) (2021)

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Article Operations Research & Management Science

Sentiment classification and aspect-based sentiment analysis on yelp reviews using deep learning and word embeddings

Eman Saeed Alamoudi et al.

Summary: Opinion mining has been used to analyze restaurant reviews on Yelp website, applying various predictive models and proposing a new unsupervised method. The reviews were categorized into different aspects based on sentiment context.

JOURNAL OF DECISION SYSTEMS (2021)

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Article Engineering, Mechanical