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Sentiment Analysis and Ontology Engineering

Overview of attention for book
Cover of 'Sentiment Analysis and Ontology Engineering'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Fundamentals of Sentiment Analysis and Its Applications
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    Chapter 2 Fundamentals of Sentiment Analysis: Concepts and Methodology
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    Chapter 3 The Comprehension of Figurative Language: What Is the Influence of Irony and Sarcasm on NLP Techniques?
  5. Altmetric Badge
    Chapter 4 Probabilistic Approaches for Sentiment Analysis: Latent Dirichlet Allocation for Ontology Building and Sentiment Extraction
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    Chapter 5 Description Logic Class Expression Learning Applied to Sentiment Analysis
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    Chapter 6 Capturing Digest Emotions by Means of Fuzzy Linguistic Aggregation
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    Chapter 7 Hyperelastic-Based Adaptive Dynamics Methodology in Knowledge Acquisition for Computational Intelligence on Ontology Engineering of Evolving Folksonomy Driven Environment
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    Chapter 8 Sentiment-Oriented Information Retrieval: Affective Analysis of Documents Based on the SenticNet Framework
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    Chapter 9 Interpretability of Computational Models for Sentiment Analysis
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    Chapter 10 Chinese Micro-Blog Emotion Classification by Exploiting Linguistic Features and SVM \(^{\textit{perf}}\)
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    Chapter 11 Social Media and News Sentiment Analysis for Advanced Investment Strategies
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    Chapter 12 Context Aware Customer Experience Management: A Development Framework Based on Ontologies and Computational Intelligence
  14. Altmetric Badge
    Chapter 13 An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief
  15. Altmetric Badge
    Chapter 14 Big Data Sentiment Analysis for Brand Monitoring in Social Media Streams by Cloud Computing
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    Chapter 15 Neuro-Fuzzy Sentiment Analysis for Customer Review Rating Prediction
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    Chapter 16 OntoLSA—An Integrated Text Mining System for Ontology Learning and Sentiment Analysis
  18. Altmetric Badge
    Chapter 17 Knowledge-Based Tweet Classification for Disease Sentiment Monitoring
Attention for Chapter 1: Fundamentals of Sentiment Analysis and Its Applications
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)

Mentioned by

twitter
2 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
232 Mendeley
Summary X Wikipedia Dimensions citations
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Chapter title
Fundamentals of Sentiment Analysis and Its Applications
Chapter number 1
Book title
Sentiment Analysis and Ontology Engineering
Published in
Studies in Computational Intelligence, March 2016
DOI 10.1007/978-3-319-30319-2_1
Book ISBNs
978-3-31-930317-8, 978-3-31-930319-2
Authors

Mohsen Farhadloo, Erik Rolland, Farhadloo, Mohsen, Rolland, Erik

Editors

Witold Pedrycz, Shyi-Ming Chen

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 232 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 232 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 30 13%
Student > Bachelor 30 13%
Student > Ph. D. Student 15 6%
Lecturer 8 3%
Student > Doctoral Student 8 3%
Other 24 10%
Unknown 117 50%
Readers by discipline Count As %
Computer Science 64 28%
Business, Management and Accounting 10 4%
Social Sciences 10 4%
Engineering 6 3%
Mathematics 4 2%
Other 19 8%
Unknown 119 51%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 February 2024.
All research outputs
#7,576,681
of 25,992,468 outputs
Outputs from Studies in Computational Intelligence
#1
of 1 outputs
Outputs of similar age
#99,255
of 316,000 outputs
Outputs of similar age from Studies in Computational Intelligence
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 4.0. This one scored the same or higher as 0 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 316,000 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them

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