The effects of customer online reviews on sales performance: The role of mobile phone’s quality characteristics

Liu, Huiming; Wu, Shaohua; Zhong, Chongjun; Liu, Ying

doi:10.1016/j.elerap.2022.101229

Cited by 7 publications

(3 citation statements)

References 65 publications

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“…Dataset size [23], [25], [29], [31], [44], [45] <5,000 [20], [22], [26], [30], [43], [46] 5,000-20,000 [24], [36], [38], [47] 20,000-50,000 [21] 50,000-100,000 [33], [34], [35], [40] >100,000 [27], [28], [32], [37], [39], [41], [42] Not available…”

Section: Literaturementioning

confidence: 99%

“…Performance metric [21], [25], [41], [47] Accuracy [28], [32] Accuracy, precision, recall [30], [44] Accuracy, F1-score [20], [23], [24], [26], [29], [31], [36], [37] Accuracy, precision, recall, F1-score [22], [27] Precision, recall, F1-score [38] F1-score [34] Perception score [46] Mapping quality characteristic [40] Relationship (online reviews-hotel sales) [43] Classify user component [33] Confusion matrix Consequently, it is deemed proficient at classifying forthcoming values. According to the data presented in Table 8, it can be observed that the random forest technique exhibits the highest level of accuracy among the ML algorithms, achieving a remarkable accuracy rate of 99.2% when applied to the TripAdvisor dataset.…”

Section: Literaturementioning

confidence: 99%

See 1 more Smart Citation

Text Classification on Customer Feedback: A Systematic Literatures Review

Sidek,

Syed Ahmad,

Kumar

et al. 2024

IJEECS

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User feedback in text classification serves multiple purposes, including refining models, enhancing datasets, adapting to user preferences, identifying emerging topics, and evaluating system performance, all of which contribute to the creation of more effective and user-centric classification systems. Many text classification techniques, including data mining, machine learning, and deep learning approaches, have been employed in previous literature, each making significant contributions to the field. This paper aims to contribute by guiding researchers seeking commonly used classification techniques and evaluation metrics in text processing. Additionally, it identifies the classification technique that generates higher accuracy and works as a basis for researchers to synthesize studies within their respective fields. PRISMA methodology is adapted to systematically review 28 current literatures on text classification on user feedback. The results obtained are guided by four research questions; paper distribution year, dataset source and size; evaluation metric and model accuracy. The review has shown that support vector machines (SVM) are frequently employed and consistently achieve high levels of accuracy as high as 97.17% with various datasets used. The future direction of this work could explore models that integrate sentiment analysis and natural language understanding to more accurately capture nuanced user opinions and preferences.

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Section: Literaturementioning

confidence: 99%

Section: Literaturementioning

confidence: 99%

Text Classification on Customer Feedback: A Systematic Literatures Review

Sidek,

Syed Ahmad,

Kumar

et al. 2024

IJEECS

View full text Add to dashboard Cite

show abstract

“…Online surveys and mobile research have made data collection more accessible and cost-effective on a global scale. These methodologies allow businesses to gather insights from diverse audiences quickly and efficiently [83][84][85].…”

Section: Online Surveys and Mobile Researchmentioning

confidence: 99%

Emerging Trends and Innovative Methods in Global Marketing: A Review Paper

Hosseini,

Mohammad

2023

focsci

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In today's rapidly evolving business landscape, global marketing has become a critical area of focus for organizations seeking to expand their reach and tap into new markets. This review paper aims to explore the emerging trends and innovative methods in global marketing that have emerged in recent years. It provides a comprehensive analysis of key strategies, tools, and technologies that are reshaping the field and discusses their implications for businesses operating on a global scale. The findings of this paper offer valuable insights for marketers and businesses looking to stay ahead of the curve in an increasingly interconnected world.

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