Efficient utilization of pre-trained models: A review of sentiment analysis via prompt learning
K Bu, Y Liu, X Ju - Knowledge-Based Systems, 2024 - Elsevier
Sentiment analysis is one of the traditional well-known tasks in Natural Language
Processing (NLP) research. In recent years, Pre-trained Models (PMs) have become one of …
Processing (NLP) research. In recent years, Pre-trained Models (PMs) have become one of …
A survey on information diffusion in online social networks: Models and methods
M Li, X Wang, K Gao, S Zhang - Information, 2017 - mdpi.com
By now, personal life has been invaded by online social networks (OSNs) everywhere. They
intend to move more and more offline lives to online social networks. Therefore, online …
intend to move more and more offline lives to online social networks. Therefore, online …
Sentiment of emojis
There is a new generation of emoticons, called emojis, that is increasingly being used in
mobile communications and social media. In the past two years, over ten billion emojis were …
mobile communications and social media. In the past two years, over ten billion emojis were …
A survey of Twitter research: Data model, graph structure, sentiment analysis and attacks
Twitter is the third most popular worldwide Online Social Network (OSN) after Facebook and
Instagram. Compared to other OSNs, it has a simple data model and a straightforward data …
Instagram. Compared to other OSNs, it has a simple data model and a straightforward data …
Unsupervised sentiment analysis with emotional signals
The explosion of social media services presents a great opportunity to understand the
sentiment of the public via analyzing its large-scale and opinion-rich data. In social media, it …
sentiment of the public via analyzing its large-scale and opinion-rich data. In social media, it …
An overview of sentiment analysis in social media and its applications in disaster relief
Sentiment analysis refers to the class of computational and natural language processing
based techniques used to identify, extract or characterize subjective information, such as …
based techniques used to identify, extract or characterize subjective information, such as …
Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment
Current disaster management procedures to cope with human and economic losses and to
manage a disaster's aftermath suffer from a number of shortcomings like high temporal lags …
manage a disaster's aftermath suffer from a number of shortcomings like high temporal lags …
Learning from the ubiquitous language: an empirical analysis of emoji usage of smartphone users
Emojis have been widely used to simplify emotional expression and enrich user experience.
As an interesting practice of ubiquitous computing, emojis are adopted by Internet users …
As an interesting practice of ubiquitous computing, emojis are adopted by Internet users …
Sentix: A sentiment-aware pre-trained model for cross-domain sentiment analysis
Pre-trained language models have been widely applied to cross-domain NLP tasks like
sentiment analysis, achieving state-of-the-art performance. However, due to the variety of …
sentiment analysis, achieving state-of-the-art performance. However, due to the variety of …
SentiDiff: combining textual information and sentiment diffusion patterns for Twitter sentiment analysis
Twitter sentiment analysis has become a hot research topic in recent years. Most of existing
solutions to Twitter sentiment analysis basically only consider textual information of Twitter …
solutions to Twitter sentiment analysis basically only consider textual information of Twitter …