Topic-level sentiment analysis of social media data using deep learning
Due to the inception of Web 2.0 and freedom to facilitate the dissemination of information,
sharing views, expressing opinions with regards to current world level events, services …
sharing views, expressing opinions with regards to current world level events, services …
Short text topic modelling approaches in the context of big data: taxonomy, survey, and analysis
Social media platforms such as (Twitter, Facebook, and Weibo) are being increasingly
embraced by individuals, groups, and organizations as a valuable source of information …
embraced by individuals, groups, and organizations as a valuable source of information …
Improve topic modeling algorithms based on Twitter hashtags
Today with increase using social media, a lot of researchers have interested in topic
extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find …
extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find …
Using machine learning to improve lead times in the identification of emerging customer needs
In recent years, computational approaches for automatically extracting the voice of the
customer from user generated content have been proposed. These studies have tackled the …
customer from user generated content have been proposed. These studies have tackled the …
Research on topic recognition of network sensitive information based on SW-LDA model
G Xu, X Wu, H Yao, F Li, Z Yu - IEEE access, 2019 - ieeexplore.ieee.org
The mining of network sensitive information is of great significance for understanding the
social stability of the network. Obtaining the network public opinion of sensitive information is …
social stability of the network. Obtaining the network public opinion of sensitive information is …
Prediction of future customer needs using machine learning across multiple product categories
In recent years, computational approaches for extracting customer needs from user
generated content have been proposed. However, there is a lack of studies that focus on …
generated content have been proposed. However, there is a lack of studies that focus on …
Topic modelling through the bibliometrics lens and its technique
Topic modelling (TM) is a significant natural language processing (NLP) task and is
becoming more popular, especially, in the context of literature synthesis and analysis …
becoming more popular, especially, in the context of literature synthesis and analysis …
Topic Modeling for Short Texts: A Novel Modeling Method
Topic modeling is one of the major concerns in the short texts area, and mining these texts
could uncover meaningful insights. However, the extreme short texts' sparsity and imbalance …
could uncover meaningful insights. However, the extreme short texts' sparsity and imbalance …
SenU-PTM: a novel phrase-based topic model for short-text topic discovery by exploiting word embeddings
Purpose Topic model has been widely applied to discover important information from a vast
amount of unstructured data. Traditional long-text topic models such as Latent Dirichlet …
amount of unstructured data. Traditional long-text topic models such as Latent Dirichlet …
Microblog hot topics detection based on VSM and HMBTM model fusion
Q Liqing, J Wei, L Haiyan, F **n - IEEE Access, 2019 - ieeexplore.ieee.org
With the rapid development of social media such as Twitter and Sina microblog, short texts
are becoming more and more popular. However, because of the sparsity of word co …
are becoming more and more popular. However, because of the sparsity of word co …