Evaluation of Chinese Sentiment Analysis APIs Based on Online Reviews

Tang, Tiantian; Huang, Liqiang; Chen, Y.

doi:10.1109/ieem45057.2020.9309968

Cited by 9 publications

(5 citation statements)

References 5 publications

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“…Employing Natural Language Processing (NLP) tools for Chinese text analysis can facilitate comprehensive semantic and sentiment analysis in this context. Notably, the use of SnowNLP 4 , a well-established Python library for Chinese sentiment analysis, is recommended for its proven efficacy in deciphering the intricate nuances of Chinese semantic environments, especially for sentiment analysis on platforms like Weibo [24,30,34,56,71].…”

Section: Methodsmentioning

confidence: 99%

Decoding Social Sentiment in DAO: A Comparative Analysis of Blockchain Governance Communities

Quan,

Wu,

Deng

et al. 2023

Preprint

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Blockchain technology is leading a revolutionary transformation across diverse industries, with effective governance standing as a critical determinant for the success and sustainability of blockchain projects. Community forums, pivotal in engaging decentralized autonomous organizations (DAOs), wield a substantial impact on blockchain governance decisions. Concurrently, Natural Language Processing (NLP), particularly sentiment analysis, provides powerful insights from textual data. While prior research has explored the potential of NLP tools in social media sentiment analysis, a gap persists in understanding the sentiment landscape of blockchain governance communities. The evolving discourse and sentiment dynamics on the forums of top DAOs remain largely unknown. This paper delves deep into the evolving discourse and sentiment dynamics on the public forums of leading DeFi projects—Aave, Uniswap, Curve Dao, Aragon, Yearn.finance, Merit Circle, and Balancer—placing a primary focus on discussions related to governance issues. Despite differing activity patterns, participants across these decentralized communities consistently express positive sentiments in their Discord discussions, indicating optimism towards governance decisions. Additionally, our research suggests a potential interplay between discussion intensity and sentiment dynamics, indicating that higher discussion volumes may contribute to more stable and positive emotions. The insights gained from this study are valuable for decision-makers in blockchain governance, underscoring the pivotal role of sentiment analysis in interpreting community emotions and its evolving impact on the landscape of blockchain governance. This research significantly contributes to the interdisciplinary exploration of the intersection of blockchain and society, with a specific emphasis on the decentralized blockchain governance ecosystem. We provide our data and code for replicability as open access on GitHub.

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Section: Methodsmentioning

confidence: 99%

Decoding Social Sentiment in DAO: A Comparative Analysis of Blockchain Governance Communities

Quan,

Wu,

Deng

et al. 2023

Preprint

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“…Shopping experience is an important experience in creating a customer mindset, related to what they expect from online retail. Tang et al, (2022)stated that customers who have more flying hours in shopping tend to continue doing this activity. Massara et al, (2019)believes that customer satisfaction in shopping is the success of the purchase and the satisfaction that has been obtained previously can improve customer performance.…”

Section: Figure 2 10 Largest Retailers In Indonesiamentioning

confidence: 99%

The Influence of Shopping Experience and Customer Engagement on Customer Loyalty of Alfagift Users Through Customer Satisfaction at Alfamart, Turen District

Chodriyah,

Haryanto,

Harsono

2023

JEFMS

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This research aims to analyze the influence of shopping experience and customer engagement on customer satisfaction, analyze the influence of shopping experience and customer engagement on customer loyalty, analyze the influence of customer satisfaction on customer loyalty and analyze the influence of shopping experience and customer engagement on customer loyalty through customer satisfaction. The sample in this study was 100 respondents. The data analysis technique uses path analysis. The analysis results show that shopping experience and customer engagement influence customer satisfaction. Shopping experience and customer engagement influence customer loyalty. Customer satisfaction influences customer loyalty. Shopping experience and customer engagement influence customer loyalty through customer satisfaction.

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“…SnowNLP is a class library for processing Chinese text content in Python, which is widely used by researchers for Chinese sentiment analysis [64][65][66]. SnowNLP provides a plain Bayesian-based method for calculating the sentiment tendency of a text.…”

Section: Appendix a Linguistic Inquiry And Word Count (Liwc)mentioning

confidence: 99%

How Do Team-Level and Individual-Level Linguistic Styles Affect Patients’ Emotional Well-Being—Evidence from Online Doctor Teams

Liu

Zhou

Chi

2023

IJERPH

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Background: In the post-epidemic era, online medical care is developing rapidly, and online doctor teams are attracting attention as a high-quality online medical service model that can provide more social support for patients. Methods: Using online doctor teams on the Haodf.com platform as the research subject, this study investigates the key factors in the process of doctor–patient communication, which affects patients’ emotional well-being. We also explore the different roles played by doctors as leaders and non-leaders in doctor–patient communication. From the perspective of language style, we select representative factors in the process of doctor–patient communication, namely the richness of health vocabulary, the expression of emotions, and the use of health-related terms (including perceptual words and biological words). We extract both team-level and individual-level linguistic communication styles through textual and sentiment analysis methods and empirically analyze their effects on patients’ emotional well-being using multiple linear regression models. Results: The results show that the expression of positive emotions by the team and attention to patients’ perceptions and biological conditions benefit patients’ emotional well-being. Leaders should focus on the emotional expression, whereas non-leaders should focus on the use of perceptual and biological words. Conclusions: This study expands the application of linguistic styles in the medical field and provides a practical basis for improving patients’ emotional well-being.

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Evaluation of Chinese Sentiment Analysis APIs Based on Online Reviews

Cited by 9 publications

References 5 publications

Decoding Social Sentiment in DAO: A Comparative Analysis of Blockchain Governance Communities

Decoding Social Sentiment in DAO: A Comparative Analysis of Blockchain Governance Communities

The Influence of Shopping Experience and Customer Engagement on Customer Loyalty of Alfagift Users Through Customer Satisfaction at Alfamart, Turen District

How Do Team-Level and Individual-Level Linguistic Styles Affect Patients’ Emotional Well-Being—Evidence from Online Doctor Teams

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