Off-The-Shelf Artificial Intelligence Technologies for Sentiment and Emotion Analysis: A Tutorial on Using IBM Natural Language Processing

Carvalho, Arthur; Levitt, Adam; Levitt, Seth; Khaddam, Edward; Benamati, John

doi:10.17705/1cais.04443

Cited by 27 publications

(22 citation statements)

References 25 publications

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“…A sentiment analysis of consumer comments on each COVID-19 announcement on Twitter conducted using IBM Natural Language Processing was used to identify consumer emotion based on how positive or negative a consumer comment was. IBM Natural Language Processing could provide overall sentiment score on specific sentences (e.g., posts or replies on Twitter) ranging from 1 (extremely positive) to −1 (extremely negative) with a score of 0 representing neutral ( Carvalho et al, 2019 ). As suggested in the product recall crisis literature ( Hsu & Lawrence, 2016 ), the most market reaction occurs within six days after the product recall announcement date.…”

Section: Methodsmentioning

confidence: 99%

Eliciting positive emotion through strategic responses to COVID-19 crisis: Evidence from the tourism sector

Wang

Filieri

et al. 2022

Tourism Management

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While social media are effective means of communicating with adverse customer emotions during a crisis, it remains unclear how tourism organisations can respond to pandemic crisis on social media to prevent negative aftermaths. Using a set-theoretical approach, we investigate how COVID-19 response strategies and linguistic cues of responses are intertwined to evoke positive emotions among consumers. This study entails a qualitative content analysis of tourism organisations' COVID-19 announcements and a social media analytics approach that captures consumers’ emotional reactions to these announcements via their Twitter replies. Our results extend some well-established findings in the tourism crisis literature by suggesting that combining innovative response strategy, argument quality, and assertive language can reinforce positive emotions during the COVID-19 crisis. Taking organisational characteristics into consideration, we suggest that young established hotels utilize innovative response strategies, whereas retrenchment response strategies for all types of restaurants should be avoided during the COVID-19 crisis.

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Section: Methodsmentioning

confidence: 99%

Eliciting positive emotion through strategic responses to COVID-19 crisis: Evidence from the tourism sector

Wang

Filieri

et al. 2022

Tourism Management

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“…Effective stakeholder engagement helps organisations build stronger stakeholder relationship, consistent with stakeholder theory. As presented in Figure 1, both the themes and the emotion of the tweets can be used by organisations in their stakeholder communication and interaction (Andriof et al, 2002; Figure 1 Conceptual framework for effective stakeholder engagement using social media Information Content -Themes (Manetti et al 2017, Jung et al 2018, Gómez-Carrasco et al 2021, Chong and Momin, 2021 Sentiment -Positive, Negative, Neutral (Carvalho, et al 2019;Duncombe, 2019) Stakeholder Communication and Interaction (Morsing and Schultz, 2006;Lawrence, 2002) Emotive language (Bartsch and Hübner, 2005) Emotional expressions -Anger, Disgust, Fear, Joy, Sadness (Kwon, et al, 2013;Pang and Ng, 2016)…”

Section: Proposed Conceptual Frameworkmentioning

confidence: 99%

Stakeholder engagement during COVID-19: evidence from corporate use of Twitter

Momin

Chong

2022

SRJ

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Purpose This study aims to investigate how New Zealand companies use Twitter to communicate and engage effectively with stakeholders during the COVID-19 pandemic. Design/methodology/approach This study proposes a conceptual framework for effective stakeholder engagement by using social media to analyse the themes and emotion of company tweets during the COVID-19 pandemic in New Zealand. The engagement of stakeholders with these tweets is also examined. This study argues that companies use selected themes and emotive language to connect with their stakeholders. Findings The findings show that selective themes and emotions are useful in company COVID-19 tweets to engage with the stakeholders. COVID-19 tweets contained significantly more emotion than non-COVID tweets, with emotions that can convey empathy being the most common. By presenting themselves as real, personable and empathetic towards others through emotive language, companies can engage in more meaningful and ethical way with their stakeholders. Practical implications The paper has implications for managing company communications by providing empirical evidence that both the themes and emotion expressed in the messages are important for effective stakeholder engagement in social media. Originality/value The conceptual framework for effective stakeholder engagement using social media is novel and can be used to evaluate and investigate stakeholder engagement during a global crisis.

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“…This synchronisation of AI with the cloud necessitates tremendous knowledge, resources, and financial investment if it is to be worthwhile for businesses. It is only when cloud computing and AI systems are properly integrated that companies will be able to utilise a wide range of powerful machine learning capabilities, such as image recognition and natural language processing [64,65]. As a result, additional businesses will follow suit in the future.…”

Section: Open Challengesmentioning

confidence: 99%

“…Images, video, natural language processing (NLP), and robotics are some of the more recent fog computing applications that are only starting to emerge [64,65]. Fog computing's picture placement and processing is one of the most widely utilised sectors of AI in research and industry, with the goal of differentiating objects or people from one another and the capacity to classify and discriminate photos based on image processing algorithms [95].…”

Section: Open Challengesmentioning

confidence: 99%

AI for Next Generation Computing: Emerging Trends and Future Directions

Gill,

Xu,

Ottaviani

et al. 2022

Preprint

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Autonomic computing investigates how systems can achieve (user) specified "control" outcomes on their own, without the intervention of a human operator. Autonomic computing fundamentals have been substantially influenced by those of control theory for closed and open-loop systems. In practice, complex systems may exhibit a number of concurrent and inter-dependent control loops. Despite research into autonomic models for managing computer resources, ranging from individual resources (e.g., web servers) to a resource ensemble (e.g., multiple resources within a data center), research into integrating Artificial Intelligence (AI) and Machine Learning (ML) to improve resource autonomy and performance at scale continues to be a fundamental challenge. The integration of AI/ML to achieve such autonomic and self-management of systems can be achieved at different levels of granularity, from full to human-in-the-loop automation. In this article, leading academics, researchers, practitioners, engineers, and scientists in the fields of cloud computing, AI/ML, and quantum computing join to discuss current research and potential future directions for these fields. Further, we discuss challenges and opportunities for leveraging AI and ML in next generation computing for emerging computing paradigms, including cloud, fog, edge, serverless and quantum computing environments.

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Off-The-Shelf Artificial Intelligence Technologies for Sentiment and Emotion Analysis: A Tutorial on Using IBM Natural Language Processing

Cited by 27 publications

References 25 publications

Eliciting positive emotion through strategic responses to COVID-19 crisis: Evidence from the tourism sector

Eliciting positive emotion through strategic responses to COVID-19 crisis: Evidence from the tourism sector

Stakeholder engagement during COVID-19: evidence from corporate use of Twitter

AI for Next Generation Computing: Emerging Trends and Future Directions

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