scholarly journals Extracting Domain-Specific Features for Sentiment Analysis Using Simple NLP Techniques: Running Shoes Reviews

10.29007/4kf5 ◽  
2018 ◽  
Author(s):  
Antonio Moreno-Ortiz ◽  
Chantal Pérez-Hernández ◽  
Cristian Gómez-Pascual
Keyword(s):  
Sentiment Analysis ◽  
Analysis Software ◽  
Multiword Expressions ◽  
Domain Specific ◽  
First Approximation ◽  
Running Shoes ◽  
Specialized Language

This paper is a first attempt at designing a procedure to derive a domain-specific lexicon (both single words and multiword expressions) from an opinion corpus of specialized language. We use a corpus of reviews of running shoes as case study, compiled for this particular purpose. The main goal is to obtain a first approximation to the task of automatically extracting domain-specific expressions of sentiment to be used by our sentiment analysis software, Lingmotif.

scholarly journals A clarified typology of core-periphery structure in networks

2021 ◽  
Vol 7 (12) ◽  
pp. eabc9800
Author(s):  
Ryan J. Gallagher ◽  
Jean-Gabriel Young ◽  
Brooke Foucault Welles
Keyword(s):  
Dense Core ◽  
Block Model ◽  
Hub And Spoke ◽  
Block Modeling ◽  
Domain Specific ◽  
The Core ◽  
Detailed Case ◽  
Rich Diversity ◽  
Modeling Techniques

Core-periphery structure, the arrangement of a network into a dense core and sparse periphery, is a versatile descriptor of various social, biological, and technological networks. In practice, different core-periphery algorithms are often applied interchangeably despite the fact that they can yield inconsistent descriptions of core-periphery structure. For example, two of the most widely used algorithms, the k-cores decomposition and the classic two-block model of Borgatti and Everett, extract fundamentally different structures: The latter partitions a network into a binary hub-and-spoke layout, while the former divides it into a layered hierarchy. We introduce a core-periphery typology to clarify these differences, along with Bayesian stochastic block modeling techniques to classify networks in accordance with this typology. Empirically, we find a rich diversity of core-periphery structure among networks. Through a detailed case study, we demonstrate the importance of acknowledging this diversity and situating networks within the core-periphery typology when conducting domain-specific analyses.

scholarly journals Sentiment Analysis of Lockdown in India During COVID-19: A Case Study on Twitter

2020 ◽  
pp. 1-11
Author(s):  
Prasoon Gupta ◽  
Sanjay Kumar ◽  
R. R. Suman ◽  
Vinay Kumar
Keyword(s):  
Sentiment Analysis

scholarly journals Using Social Media in Tourist Sentiment Analysis: A Case Study of Andalusia during the Covid-19 Pandemic

2021 ◽  
Vol 13 (7) ◽  
pp. 3836
Author(s):  
David Flores-Ruiz ◽  
Adolfo Elizondo-Salto ◽  
María de la O. Barroso-González
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Cost Savings ◽  
Mass Scale ◽  
Tourism Sector ◽  
The Social ◽  
Analytical Tools ◽  
Media Data

This paper explores the role of social media in tourist sentiment analysis. To do this, it describes previous studies that have carried out tourist sentiment analysis using social media data, before analyzing changes in tourists’ sentiments and behaviors during the COVID-19 pandemic. In the case study, which focuses on Andalusia, the changes experienced by the tourism sector in the southern Spanish region as a result of the COVID-19 pandemic are assessed using the Andalusian Tourism Situation Survey (ECTA). This information is then compared with data obtained from a sentiment analysis based on the social network Twitter. On the basis of this comparative analysis, the paper concludes that it is possible to identify and classify tourists’ perceptions using sentiment analysis on a mass scale with the help of statistical software (RStudio and Knime). The sentiment analysis using Twitter data correlates with and is supplemented by information from the ECTA survey, with both analyses showing that tourists placed greater value on safety and preferred to travel individually to nearby, less crowded destinations since the pandemic began. Of the two analytical tools, sentiment analysis can be carried out on social media on a continuous basis and offers cost savings.

scholarly journals Deep Sentiment Analysis: A Case Study on Stemmed Turkish Twitter Data

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Harisu Abdullahi Shehu ◽  
Md. Haidar Sharif ◽  
Md. Haris Uddin Sharif ◽  
Ripon Datta ◽  
Sezai Tokat ◽  
...  
Keyword(s):  
Sentiment Analysis ◽  
Twitter Data

Building Domain-Specific Environments for Computational Science: a Case Study in Seismic Tomography

1997 ◽  
Vol 11 (3) ◽  
pp. 179-196 ◽  
Author(s):  
Janice E. Cuny ◽  
Robert A. Dunn ◽  
Steven T. Hackstadt ◽  
Christopher W. Harrop ◽  
Harold H. Hersey ◽  
...  
Keyword(s):  
Seismic Tomography ◽  
Computational Science ◽  
Domain Specific
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