Why do people (not) like me?: Mining opinion influencing factors from reviews

Bilici, Eda; Saygın, Yücel

doi:10.1016/j.eswa.2016.10.001

Cited by 20 publications

(8 citation statements)

References 37 publications

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“…James et al (2017) used LDA from patient reviews to identify common service failures in the health care domain. Bilici and Saygın (2017) used LDA from patient reviews, then applied a Bayesian network to identify common service failures and relationships among them.…”

Section: Analysis Of Unstructured Feedback For Dual Service Failure Monitoringmentioning

confidence: 99%

“…Thus, previous research methods can neither track service failure trends in the future to manage service quality nor identify the relationship between service failures. Furthermore, although a Bayesian network (Bilici & Saygın, 2017) allowed identification of consecutive service failures by learning the conditional probability between service failures, it assumes that the relationships among them is known. The method is not suitable when the relationship between service failures is not easy to identify.…”

Section: Analysis Of Unstructured Feedback For Dual Service Failure Monitoringmentioning

confidence: 99%

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Data-Driven Approach to Dual Service Failure Monitoring From Negative Online Reviews: Managerial Perspective

Joung

Kim

2021

SAGE Open

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Monitoring of dual service failures (e.g., trends in service failures and consecutive service failures) in business is emphasized for service quality management. Previous studies analyzing negative online reviews to conduct dual service failure monitoring from a managerial perspective are scarce. Numerous negative online reviews are useful sources for dual service failure monitoring because they can be easily collected at a low cost. This article proposes a data-driven approach to monitor service failure trends and consecutive service failures from negative online reviews. In the proposed approach, first a classifier is developed to categorize newly collected negative reviews into service failures by Latent Dirichlet allocation. Subsequently, a threshold value is provided to identify a new type of service failure, which was not achieved previously using a control chart. Finally, the probability of consecutive service failures is obtained by association rule mining. A case study of Uber is conducted to validate the proposed approach. The results exhibit that the proposed approach can perform dual service failure monitoring. This study can increase marketing intelligence for dynamic management of service failure and allow rapid responses to service failures.

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Section: Analysis Of Unstructured Feedback For Dual Service Failure Monitoringmentioning

confidence: 99%

Section: Analysis Of Unstructured Feedback For Dual Service Failure Monitoringmentioning

confidence: 99%

Data-Driven Approach to Dual Service Failure Monitoring From Negative Online Reviews: Managerial Perspective

Joung

Kim

2021

SAGE Open

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“…The use of mercury in traditional mining activities making it easier for them to mine gold. Many can impact public health [4], environmental degradation, which in the long term can reduce the productivity of land [5].…”

Section: Introductionmentioning

confidence: 99%

Recovery of Agricultural Areas Affected by Traditional Gold Mining: Sustainable Food Supply Stability

Golar¹,

Basir-Cyio²,

Isrun³

et al. 2021

IJDNE

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This study aims to analyze the recovery of the agricultural area’s function affected by the Poboya traditional gold mining in supporting the stability of sustainable food supply. We began the research by examining the existing mining land conditions through spatial analysis (land cover and land use changes from 2010 to 2019). Apart from that, it also analyzed the land’s health was through the soil’s physical and chemical properties, especially mercury. The observation proved that changes in the land’s cover and uses lead to decreased land quality and degradation. The existing condition showed heavy metals, particularly mercury, mostly polluted agricultural land in the mining area. The model design produced by this study may 1) emphasize land arrangement; 2) revegetation design with forestry, plantation, and food crops; 3) domesticated plant; and 4) environmental monitoring, concerning monitoring of soil quality, monitoring of erosion and sedimentation, water quality, acid mine drainage, successful revegetation, and others. These four aspects expect to help suppress the rate of land degradation in agriculture located in ex-mining areas and reduce forest destruction in the Grand Forest Park area.

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“…On the one hand, explaining why an item is suggested might fail to help the user's decisionmaking because (s)he disagrees with the rationale behind the suggestions. On the other hand, as review summarization conveys information about the experience with items, it is useful to highlight pros and cons of products and services [3,12]. However, it generates descriptions that make direct reference to specific item features; e.g., see [7,31,41].…”

Section: Introductionmentioning

confidence: 99%

A Service-oriented Perspective on the Summarization of Recommendations: Preliminary Experiment

Mauro

Ardissono

et al. 2021

Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization

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The explanation and justification of recommender systems' results are challenging research tasks. On the one hand, a model-based description that clarifies the reasoning approach behind the suggestions might be difficult to understand, or it might fail to convince the user, if (s)he does not agree on the applied inference mechanism. On the other hand, an aspect-based justification based on few characteristics might provide a partial view of items or, if more detailed, it might overload the user with too much information.In order to address these issues, we propose a visual model aimed at justifying recommendations from a holistic perspective. Our model is based on a service-oriented summary of consumers' experience with items. We use the Service Journey Maps to extract data about the experience with services from online reviews, and to generate a visual summary of such feedback, based on evaluation dimensions that refer to all the stages of service fruition. Thanks to a graphical representation of these dimensions (based on bar graphs), and on the provision of on-demand data about the associated aspects of items, our model enables the user to overview the recommendation list and to quickly identify the subset of results that deserve to be inspected in detail for a final selection decision. A preliminary user study, based on the Apartment Monitoring application, has provided encouraging results about the usefulness and efficacy of our model to enhance user awareness and decisionmaking in the presence of medium-size recommendation lists. CCS CONCEPTS• Information systems → Web searching and information discovery; Recommender systems.

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Why do people (not) like me?: Mining opinion influencing factors from reviews

Cited by 20 publications

References 37 publications

Data-Driven Approach to Dual Service Failure Monitoring From Negative Online Reviews: Managerial Perspective

Data-Driven Approach to Dual Service Failure Monitoring From Negative Online Reviews: Managerial Perspective

Recovery of Agricultural Areas Affected by Traditional Gold Mining: Sustainable Food Supply Stability

A Service-oriented Perspective on the Summarization of Recommendations: Preliminary Experiment

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