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Enhancing churn forecasting with sentiment analysis of steam reviews
7 references·1 citing·39 second hop
Enhancing churn forecasting with sentiment analysis of steam reviews (2024)Enhancing churn forecasting with sentimen…An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes (2023)An adaptive learning approach…Theory building with big data-driven research – Moving away from the “What” towards the “Why” (2020)Theory building with big data…Customer Churn Prediction Model and Identifying Features to Increase Customer Retention based on User Generated Content (2020)Customer Churn Prediction Mod…Combining Sequential and Aggregated Data for Churn Prediction in Casual Freemium Games (2019)Combining Sequential and Aggr…Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods (2018)Cross-company customer churn …Twitter opinion mining predicts broadband internet's customer churn rate (2017)Twitter opinion mining predic…Customer churn prediction in the telecommunication sector using a rough set approach (2016)Customer churn prediction in …ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn Feature Engineering (2025)ChurnKB: A Generative AI-Enri…Customer Switching Behavior in Service Industries: An Exploratory Study (1995)Investigating drivers of bank loyalty: the complex relationship between image, service quality and satisfaction (1998)Handling class imbalance in customer churn prediction (2008)Machine-Learning Techniques for Customer Retention: A Comparative Study (2018)Churn Prediction in Telecommunication using Logistic Regression and Logit Boost (2020)A Systematic Review of the Causes and Consequences of Price Hikes in Bangladesh (2023)Tata Bahasa Baku Bahasa Indonesia (1988)Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment (2010)Twitter mood predicts the stock market (2011)Telecommunication Service Subscriber Churn Likelihood Prediction Analysis Using Diverse Machine Learning Model (2020)What social media sentiment tells us about why customers churn (2022)Data Cleaning: Problems and Current Approaches. (2000)Understanding customer satisfaction and loyalty: An empirical study of mobile instant messages in China (2009)An Empirical Study on Customer Segmentation by Purchase Behaviors Using a RFM Model and K-Means Algorithm (2020)From user-generated data to data-driven innovation: A research agenda to understand user privacy in digital markets (2021)Deep Churn Prediction Method for Telecommunication Industry (2023)On the Profitability of Long-Life Customers in a Noncontractual Setting: An Empirical Investigation and Implications for Marketing (2000)Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Sentiment Analysis Based Churn Prediction in Mobile Games using Word Embedding Models and Deep Learning Algorithms (2020)A comprehensive survey on customer churn analysis studies (2025)Data-Driven Decision Support in SaaS Cloud-Based Service Models (2025)Customer retention, loyalty, and satisfaction in the German mobile cellular telecommunications market (2001)A comparison of machine learning techniques for customer churn prediction (2015)Customer churn prediction in telecom using machine learning in big data platform (2019)Prediction of Customer Churn in Telecom Industry: A Machine Learning Perspective (2021)An Ensemble Model for Predicting Retail Banking Churn in the Youth Segment of Customers (2022)Structural Equation Modeling and Regression: Guidelines for Research Practice (2000)Design science in information systems research (2004)Design Science in Information Systems Research1 (2004)Public and private value creation using artificial intelligence: An empirical study of AI voice robot users in Chinese public sector (2021)User-Generated Content behavior and digital tourism services: A SEM-neural network model for information trust in social networking sites (2021)Data mining for direct marketing: problems and solutions (1998)The effects of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunication services (2004)ChurnNet: Deep Learning Enhanced Customer Churn Prediction in Telecommunication Industry (2024)Enhancing customer retention in telecom industry with machine learning driven churn prediction (2024)Customer Churn Prediction: A Systematic Review of Recent Advances, Trends, and Challenges in Machine Learning and Deep Learning (2025)The Varieties of Consumption Experience: Comparing Two Typologies of Emotion in Consumer Behavior (1986)Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting (2004)Understanding Customer Experience Throughout the Customer Journey (2016)
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References

  • 2020Theory building with big data-driven research – Moving away from the “What” towards the “Why”301 cited
  • 2016Customer churn prediction in the telecommunication sector using a rough set approach222 cited
  • 2018Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods102 cited
  • 2023An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes76 cited
  • 2020Customer Churn Prediction Model and Identifying Features to Increase Customer Retention based on User Generated Content32 cited
  • 2019Combining Sequential and Aggregated Data for Churn Prediction in Casual Freemium Games24 cited
  • 2017Twitter opinion mining predicts broadband internet's customer churn rate18 cited

Cited by

  • 2025ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn Feature Engineering13 cited

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