A survey of sentiment analysis in social media
Sentiments or opinions from social media provide the most up-to-date and inclusive
information, due to the proliferation of social media and the low barrier for posting the …
information, due to the proliferation of social media and the low barrier for posting the …
Like it or not: A survey of twitter sentiment analysis methods
A Giachanou, F Crestani - ACM Computing Surveys (CSUR), 2016 - dl.acm.org
Sentiment analysis in Twitter is a field that has recently attracted research interest. Twitter is
one of the most popular microblog platforms on which users can publish their thoughts and …
one of the most popular microblog platforms on which users can publish their thoughts and …
A survey on semi-supervised learning
JE Van Engelen, HH Hoos - Machine learning, 2020 - Springer
Semi-supervised learning is the branch of machine learning concerned with using labelled
as well as unlabelled data to perform certain learning tasks. Conceptually situated between …
as well as unlabelled data to perform certain learning tasks. Conceptually situated between …
Sentiment analysis: A survey on design framework, applications and future scopes
M Bordoloi, SK Biswas - Artificial intelligence review, 2023 - Springer
Sentiment analysis is a solution that enables the extraction of a summarized opinion or
minute sentimental details regarding any topic or context from a voluminous source of data …
minute sentimental details regarding any topic or context from a voluminous source of data …
A framework for fake review detection in online consumer electronics retailers
R Barbado, O Araque, CA Iglesias - Information Processing & Management, 2019 - Elsevier
The impact of online reviews on businesses has grown significantly during last years, being
crucial to determine business success in a wide array of sectors, ranging from restaurants …
crucial to determine business success in a wide array of sectors, ranging from restaurants …
The role of text pre-processing in sentiment analysis
It is challenging to understand the latest trends and summarise the state or general opinions
about products due to the big diversity and size of social media data, and this creates the …
about products due to the big diversity and size of social media data, and this creates the …
[HTML][HTML] An influence maximization method based on crowd emotion under an emotion-based attribute social network
Most research on influence maximization focuses on the network structure features of the
diffusion process but lacks the consideration of multi-dimensional characteristics. This paper …
diffusion process but lacks the consideration of multi-dimensional characteristics. This paper …
[PDF][PDF] Predicting polarities of tweets by composing word embeddings with long short-term memory
In this paper, we introduce Long Short-Term Memory (LSTM) recurrent network for twitter
sentiment prediction. With the help of gates and constant error carousels in the memory …
sentiment prediction. With the help of gates and constant error carousels in the memory …
[PDF][PDF] Learning semantic representations of users and products for document level sentiment classification
Neural network methods have achieved promising results for sentiment classification of text.
However, these models only use semantics of texts, while ignoring users who express the …
However, these models only use semantics of texts, while ignoring users who express the …
A survey of signed network mining in social media
Many real-world relations can be represented by signed networks with positive and negative
links, as a result of which signed network analysis has attracted increasing attention from …
links, as a result of which signed network analysis has attracted increasing attention from …