EMFSA: Emoji-based multifeature fusion sentiment analysis
Hongmei Tang1,2, Wenzhong Tang1, Dixiongxiao Zhu1
1School of Computer Science and Engineering, Beihang University, Beijing, China.
Plos One
|September 19, 2024
Summary
This study introduces an emoji-based multifeature fusion sentiment analysis model (EMFSA) to improve short text analysis. The EMFSA model enhances emotional expression and sentiment accuracy by integrating emoji, topic, and text features.
Area of Science:
- Natural Language Processing
- Computational Linguistics
- Artificial Intelligence
Background:
- Short texts on social media often lack emotional depth and feature richness.
- Challenges include semantic ambiguity and sparse data, hindering accurate sentiment analysis.
Purpose of the Study:
- To enhance sentiment analysis accuracy for short texts.
- To propose an effective model for extracting emotional semantics from short texts.
Main Methods:
- Developed an emoji-based multifeature fusion sentiment analysis model (EMFSA).
- Employed a pretraining method for feature extraction and a sentiment- and emoji-masked language model.
- Utilized a cross-attention mechanism for multifeature fusion, integrating emoji, topic, and text features.
Main Results:
- The EMFSA model demonstrated significant accuracy improvements on three public datasets.
- Achieved accuracy gains of 2.3%, 10.9%, and 2.7% compared to baseline methods.
- Effectively enhanced semantic expressions of emotions and sentiment representation accuracy.
Conclusions:
- The proposed EMFSA model effectively addresses limitations in short text sentiment analysis.
- Multifeature fusion, particularly incorporating emoji semantics, is crucial for improving accuracy.
- The model shows strong potential for real-world applications in social media analysis.
More Related Videos
Related Concept Videos
01:24Tagging and Fusion Proteins
6.6K
Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
6.6K
02:34Empathy
9.6K
Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor.
9.6K
01:41Affinity and Avidity
35.9K
Overview
35.9K
00:42Cross-reactivity
31.0K
Overview
31.0K
01:22Motional Emf
3.2K
Magnetic flux depends on three factors: the strength of the magnetic field, the area through which the field lines pass, and the field's orientation with respect to the surface area. If any of these quantities vary, a corresponding variation in magnetic flux occurs. If the area through which the magnetic field lines are passing changes, then the magnetic flux also changes. This change in the area can be of two types: the flux through the rectangular loop increases as it moves into the...
3.2K
01:14Muscles for Facial Expressions
1.9K
The craniofacial muscles are a collection of approximately 20 thin skeletal muscles situated beneath the skin of the face and scalp. These muscles, primarily responsible for the vast array of human facial expressions, originate from the bones or fibrous structures of the skull and extend outwards to connect with the skin. While most skeletal muscles in the body are enveloped in thick fascia, facial muscles generally have a more delicate fascial covering, with the buccinator muscle being a...
1.9K