… sentiments to improve our results. The proposed architecture of our method of suicide
detection based on social network, machine learning and semantic analysis, is shown in Figure 1. …

… network levels. We demonstrate that sentiment prediction that solely relies on social network
… the trade-off between the sentiment prediction performance and the available information. …

… their sentiments. In this paper, we propose Polaris, a system for analyzing and predicting
users’ sentimental trajectories for events analyzed in real time out of the massive social media …

… ontology (GSO) as well as the first framework targeting on the problem of GIF sentiment
analysis for social networks. This dataset uses SentiPair Sequence to model the image …

… the public sentiment. This paper studies the sentiment prediction task over Twitter using
machine-learning techniques, with the consideration of Twitter-specific social network structure …

… social network analysis, in particular applied to sentiment analysis and community discovery
in social networks. … in web/text mining, sentiment analysis, social network analysis, e-justice, …

… This work presents and assesses the power of various volumetric, sentiment, and social
network approaches to predict crucial decisions from online social media platforms. The views of …

… features associated with the text in social network scenarios, especially the different users
and … of the social network platforms, combine these textual information with the sentiment time …

… for prediction tasks. To address this issue, we model sentiment prediction as a task of time
series prediction and propose a Time-Enhanced Neighbor-Aware network on irregular time …

… We represent the given social network as a signed graph G = (V,E,x), where the vertices V
represent people; the edges E, relationships between people in V; and the sign vector x ∈ {0,1…