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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …