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 …

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 …

Attributed network embedding aims to seek low-dimensional vector representations for
nodes in a network, such that original network topological structure and node attribute …

The growth of social media over the last decade has revolutionized the way individuals
interact and industries conduct business. Individuals produce data at an unprecedented rate …

Sentiment analysis is one of the prominent fields of data mining that deals with the
identification and analysis of sentimental contents generally available at social media …

Network embedding is to learn low-dimensional vector representations for nodes in a
network. It has shown to be effective in a variety of tasks such as node classification and link …

Twitter is a microblogging site in which users can post updates (tweets) to friends (followers).
It has become an immense dataset of the so-called sentiments. In this paper, we introduce …

Happiness and other emotions spread between people in direct contact, but it is unclear
whether massive online social networks also contribute to this spread. Here, we elaborate a …

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 …

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 …