Spatiotemporal‐based sentiment analysis on tweets for risk assessment of event using deep learning approach

In recent years, increasing attention is being paid to sentiment analysis on microblogging platforms such as Twitter. Sentiment analysis refers to the task of detecting whether a textual item (e.g., a tweet) contains an opinion about a topic. This paper proposes a probabilistic deep learning approach for sentiments analysis. The deep learning model used is a convolutional neural network (CNN). The main contribution of this approach is a new probabilistic representation of the text to be fed as input to the CNN. This representation is a matrix that stores for each word composing the message the probability that it belongs to a positive class and the probability that it belongs to a negative class. The proposed approach is evaluated on four well-known datasets HCR, OMD, STS-gold, and a dataset provided by the SemEval-2017 Workshop. The results of the experiments show that the proposed approach competes with the state-of-the-art sentiment analyzers and has the potential to detect sentiments from textual data in an effective manner.

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CME Test for Geometric Total Plaque Area Is an Equally Powerful Phenotype Compared with Carotid Intima-Media Thickness for Stroke Risk Assessment: A Deep Learning Approach

Journal for Vascular Ultrasound ◽

10.1177/1544316718820612 ◽

2018 ◽

Vol 42 (4) ◽

pp. 204-204

Keyword(s):

Risk Assessment ◽

Deep Learning ◽

Stroke Risk ◽

Intima Media Thickness ◽

Carotid Intima Media Thickness ◽

Learning Approach ◽

Media Thickness ◽

Plaque Area ◽

Total Plaque Area

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Twitter Sentiment Analysis Model

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2021.36309 ◽

2021 ◽

Vol 9 (VII) ◽

pp. 296-302

Author(s):

Pushkar Dubey

Keyword(s):

Machine Learning ◽

Social Networks ◽

Social Media ◽

Deep Learning ◽

Sentiment Analysis ◽

Language Processing ◽

Learning Approach ◽

Analysis Model ◽

Market Place ◽

The Social

Social networks are the main resources to gather information about people’s opinion towards different topics as they spend hours daily on social media and share their opinion. Twitter is one of the social media that is gaining popularity. Twitter offers organizations a fast and effective way to analyze customers’ perspectives toward the critical to success in the market place. Developing a program for sentiment analysis is an approach to be used to computationally measure customers’ perceptions. .We use natural language processing and machine learning concepts to create a model for analysis . In this paper we are discussing how we can create a model for analysis of twittes which is trained by various nlp , machine learning and Deep learning Approach.

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