Do Spoilers Really Spoil? Using Topic Modeling to Measure the Effect of Spoiler Reviews on Box Office Revenue

Ryoo, Jun Hyun; Wang, Xin; Lu, Shijie

doi:10.1177/0022242920937703

Cited by 33 publications

(20 citation statements)

References 55 publications

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“…To achieve the optimal results, we first fine-tuned the model’s hyperparameters. We removed topics with less than 1% of the total dataset; that is, topics containing less than 74 reviews would be ignored by the algorithm (Ryoo, Wang, and Lu 2021). We also used the CountVector module under the Scikit-Learn library to convert the reviews into a matrix of token counts with a maximum of 2-g and remove common English stopwords (Pedregosa et al 2011).…”

Section: Methodsmentioning

confidence: 99%

Customer Emotions in Service Robot Encounters: A Hybrid Machine-Human Intelligence Approach

Filieri

Lin

et al. 2022

Journal of Service Research

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Understanding consumer emotions arising from robot-customers encounters and shared through online reviews is critical for forecasting consumers’ intention to adopt service robots. Qualitative analysis has the advantage of generating rich insights from data, but it requires intensive manual work. Scholars have emphasized the benefits of using algorithms for recognizing and differentiating among emotions. This study critically addresses the advantages and disadvantages of qualitative analysis and machine learning methods by adopting a hybrid machine-human intelligence approach. We extracted a sample of 9707 customers reviews from two major social media platforms (Ctrip and TripAdvisor), encompassing 412 hotels in 8 countries. The results show that the customer experience with service robots is overwhelmingly positive, revealing that interacting with robots triggers emotions of joy, love, surprise, interest, and excitement. Discontent is mainly expressed when customers cannot use service robots due to malfunctioning. Service robots trigger more emotions when they move. The findings further reveal the potential moderation effect of culture on customer emotional reactions to service robots. The study highlights that the hybrid approach can take advantage of the scalability and efficiency of machine learning algorithms while overcoming its shortcomings, such as poor interpretative capacity and limited emotion categories.

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Section: Methodsmentioning

confidence: 99%

Customer Emotions in Service Robot Encounters: A Hybrid Machine-Human Intelligence Approach

Filieri

Lin

et al. 2022

Journal of Service Research

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“…This analysis technique, which was developed in the field of computer science and NLP, has been widely adopted by scholars to study the comments consumers share on social media about brands and products (Ryoo et al , 2021).…”

Section: Theoretical Background and Hypotheses Developmentmentioning

confidence: 99%

Do sensory reviews make more sense? The mediation of objective perception in online review helpfulness

Lopez

Garza²

2021

JRIM

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PurposeDo consumers rate reviews describing other consumers' sensory experience of a product (touch, smell, sight, hear and taste) as helpful or do they rate reviews describing more practical properties (product performance and characteristics/features) as more helpful? What is the effect of review helpfulness on purchase intention? Furthermore, why do consumers perceive sensory and non-sensory reviews differently? This study answers these questions.Design/methodology/approachThe authors analyze 447,792 Amazon reviews and perform a topic modeling analysis to extract the main topics that consumers express in their reviews. Then, the topics were used as regressors to predict the number of consumers who found the review helpful. Finally, a lab experiment was conducted to replicate the results in a more controlled environment to test the serial mediation effect.FindingsContrary to the overwhelming evidence supporting the positive effects of sensory elicitation in marketing, this study shows that sensory reviews are less likely to be helpful than non-sensory reviews. Moreover, a key reason why sensory reviews are less effective is that they decrease the objective perception of the review, a less objective review then decreases the level of helpfulness, which decreases purchase intention.Originality/valueThis study contributes to the interactive marketing field by investigating customer behavior and interactivity in online shopping sites and to the sensory marketing literature by identifying a boundary condition, the authors’ data suggest that sensory elicitations might not be processed positively by consumers when they are not directly experienced, but instead communicated by another consumer. Moreover, this study indicates how companies can encourage consumers to share more effective and helpful reviews.

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“…For example, Mustak et al [42] reviewed Artificial Intelligence in marketing using TM technology. Hyun et al [43] used TM to analyze the effects of spoilers in online reviews. Fig.…”

Section: ) Country Analysismentioning

confidence: 99%

Topic Modeling: Perspectives From a Literature Review

Grisales¹,

Robledo²,

Zuluaga

2023

IEEE Access

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Topic modeling is a Natural Language Processing technique that has gained popularity over the last ten years, with applications in multiple fields of knowledge. However, there is insufficient empirical evidence to show how this field of study has developed over the years, as well as the main models that have been applied in different contexts. The objective of this paper is to analyze the evolution of the topic modeling technique, the main areas in which it has been applied, and the models that are recommended for specific types of data. The methodology applied is based on bibliometric analysis. First, we searched the Web of Science and the Scopus databases. We then used scientometric techniques and a Tree of Science methodology, which allowed us to analyze the search results from the perspectives of classics, structure, and trends. The results show that the USA and China are among the most productive countries in this field and the applications have been mainly in the identification of sub-topics in short texts, such as social networks and blogs. The main conclusion of this work is that topic modeling is a versatile technique that can complement systematic literature reviews and that has been well-received in different academic and research contexts. The results of this study will help researchers and academics to recognize the importance of these techniques for reviewing large volumes of unstructured information, such as research articles, and in general, for systematic literature reviews.

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Do Spoilers Really Spoil? Using Topic Modeling to Measure the Effect of Spoiler Reviews on Box Office Revenue

Cited by 33 publications

References 55 publications

Customer Emotions in Service Robot Encounters: A Hybrid Machine-Human Intelligence Approach

Customer Emotions in Service Robot Encounters: A Hybrid Machine-Human Intelligence Approach

Do sensory reviews make more sense? The mediation of objective perception in online review helpfulness

Topic Modeling: Perspectives From a Literature Review

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