scholarly journals Mining Changes in User Expectation Over Time From Online Reviews

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
Tianjun Hou ◽  
Bernard Yannou ◽  
Yann Leroy ◽  
Emilie Poirson
Keyword(s):  
Conjoint Analysis ◽  
Language Processing ◽  
Online Reviews ◽  
Kano Model ◽  
Improvement Strategies ◽  
Two Generations ◽  
Product Improvement ◽  
Set Up ◽  
Successive Generations ◽  
Flow Of Information

Customers post online reviews at any time. With the timestamp of online reviews, they can be regarded as a flow of information. With this characteristic, designers can capture the changes in customer feedback to help set up product improvement strategies. Here, we propose an approach for capturing changes in user expectation on product affordances based on the online reviews for two generations of products. First, the approach uses a rule-based natural language processing method to automatically identify and structure product affordances from review text. Then, inspired by the Kano model which classifies preferences of product attributes in five categories, conjoint analysis is used to quantitatively categorize the structured affordances. Finally, changes in user expectation can be found by applying the conjoint analysis on the online reviews posted for two successive generations of products. A case study based on the online reviews of Kindle e-readers downloaded from amazon.com shows that designers can use our proposed approach to evaluate their product improvement strategies for previous products and develop new product improvement strategies for future products.

Design of GA and Ontology based NLP Frameworks for Online Opinion Mining

2019 ◽  
Vol 13 (2) ◽  
pp. 159-165
Author(s):  
Manik Sharma ◽  
Gurvinder Singh ◽  
Rajinder Singh
Keyword(s):  
Genetic Algorithm ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Opinion Mining ◽  
Hybrid Genetic Algorithm ◽  
Online Reviews ◽  
Middle Tier ◽  
Complete Set ◽  
Mining Model

Background: For almost every domain, a tremendous degree of data is accessible in an online and offline mode. Billions of users are daily posting their views or opinions by using different online applications like WhatsApp, Facebook, Twitter, Blogs, Instagram etc. Objective: These reviews are constructive for the progress of the venture, civilization, state and even nation. However, this momentous amount of information is useful only if it is collectively and effectively mined. Methodology: Opinion mining is used to extract the thoughts, expression, emotions, critics, appraisal from the data posted by different persons. It is one of the prevailing research techniques that coalesce and employ the features from natural language processing. Here, an amalgamated approach has been employed to mine online reviews. Results: To improve the results of genetic algorithm based opining mining patent, here, a hybrid genetic algorithm and ontology based 3-tier natural language processing framework named GAO_NLP_OM has been designed. First tier is used for preprocessing and corrosion of the sentences. Middle tier is composed of genetic algorithm based searching module, ontology for English sentences, base words for the review, complete set of English words with item and their features. Genetic algorithm is used to expedite the polarity mining process. The last tier is liable for semantic, discourse and feature summarization. Furthermore, the use of ontology assists in progressing more accurate opinion mining model. Conclusion: GAO_NLP_OM is supposed to improve the performance of genetic algorithm based opinion mining patent. The amalgamation of genetic algorithm, ontology and natural language processing seems to produce fast and more precise results. The proposed framework is able to mine simple as well as compound sentences. However, affirmative preceded interrogative, hidden feature and mixed language sentences still be a challenge for the proposed framework.

Validating Perceived Sustainable Design Features Using a Novel Collage Approach

2021 ◽  
pp. 1-46
Author(s):  
Nasreddine El Dehaibi ◽  
Ting Liao ◽  
Erin F. MacDonald
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Sustainable Design ◽  
Design Method ◽  
Online Reviews ◽  
Design Features ◽  
Sustainable Products ◽  
Low Correlation ◽  
Social Environmental

Abstract Designers are challenged to create sustainable products that resonate with customers, often focusing on engineered sustainability while neglecting perceived sustainability. We previously proposed a method for extracting perceived sustainable features from online reviews using annotations and natural language processing, testing our method with French press coffee carafes. We identified that perceived sustainability may not always align with engineered sustainability. We now investigate how designers can validate perceived features extracted from online reviews using a relatively new design method of collage placement where participants drag and drop products on a collage and select features from a drop-down menu. We created collage activities for participants to evaluate French press products on the three aspects of sustainability: social, environmental, and economic, and on how much they like the products. During the activity participants placed products along the two axes of the collage, sustainability and likeability, and labeled products with descriptive features. We found that participants more often selected our previously extracted features when placing products higher on the sustainability axis, validating that the perceived sustainable features resonate with users. We also measured a low correlation between the two-axes of the collage activity, indicating that perceived sustainability and likeability can be measured separately. In addition, we found that product perceptions across sustainability aspects may differ between demographics. Based on these results, we confirm that the collage is an effective tool for validating sustainability perceptions and that features perceived as sustainable from online reviews resonate with customers when thinking of various sustainability aspects.

Validating Perceived Sustainable Design Features Using a Novel Collage Approach

2021 ◽  
Author(s):  
Nasreddine El-Dehaibi ◽  
Ting Liao ◽  
Erin F. MacDonald
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Sustainable Design ◽  
Design Method ◽  
Online Reviews ◽  
Design Features ◽  
Customer Perceptions ◽  
Product Features ◽  
Social Environmental

Abstract Fierce e-commerce competition challenges designers to differentiate their products on platforms such as Amazon. To achieve this differentiation, designers must first understand how customers perceive product features. This paper builds on our previous work where we extracted features perceived as sustainable for French Press coffee carafes using annotations of Amazon reviews and natural language processing (NLP). We identified a gap between customer perceptions of sustainability and engineered sustainability. We now test our findings with a relatively new design method of collage placement and investigate how designers can use perceived features to set their products apart. We created collage activities for participants to evaluate French Press products on the three aspects of sustainability: social, environmental, and economic, and on how much they like the products. During the activity participants placed products along the two axes of the collage, sustainability and likeability, and labeled products with descriptive features that we provided. We found that participants more often selected features perceived as sustainable when placing products higher on the sustainability axis, demonstrating that these features resonated with customers. We also measured a low correlation between the two-axes of the collage activity, indicating that perceived sustainability and likeability can be measured separately. In addition, we found that product perceptions across sustainability aspects may differ between demographics. Based on these results, we confirm that features perceived as sustainable that are extracted from online reviews resonate with customers when thinking of various sustainability aspects and that the collage is an effective tool for assessing sustainability perceptions.

It's a Setup

2021 ◽  
Author(s):  
Timothy Black ◽  
Sky Keyes
Keyword(s):  
Low Income ◽  
Child Protection ◽  
Father Involvement ◽  
Child Support ◽  
Dark Side ◽  
Two Generations ◽  
New Beginnings ◽  
Low Income Families ◽  
Set Up ◽  
Childhood Traumas

The norms and expectations of father involvement have changed rapidly within one to two generations. Socially and economically marginalized fathers are being exposed to these messages through popular culture and the media; in state welfare, child protection, and probation offices; in jails, prisons, and post-release programs; and in child support and family courts. Moreover, they are being told that it is up to them to make better choices, to get themselves together, and to be involved fathers. Based on life history interviews with 138 low-income fathers, Black and Keyes show that fathers have internalized these messages and sound determined. After all, there is social worth in fatherhood, hope for creating meaningful lives or new beginnings, the fantasy of leaving something of value behind in the world, and a stake in resisting stigmatizing labels like the deadbeat dad. Most will, however, fall short for several reasons: first, while the expectations for father involvement were increasing, state and economic support for low-income families was decreasing; second, vulnerable fathers often lack viable models to guide them; third, living in dangerous neighborhoods compromises fatherhood and leaves fathers at odds with dominant institutional narratives about being nurturing fathers; and fourth, the dark side of poverty, inscribed on bodies and minds, leaves some struggling with childhood traumas and unhealthy routines to mitigate or numb these painful developmental disruptions. Consequently, the authors assert that without transformative economic, political, and social change that would facilitate and support engaged and nurturing fatherhood, these fathers are being “set up.”

EXPRESS: Attribute Embedding: Learning Hierarchical Representations of Product Attributes from Consumer Reviews

2021 ◽  
pp. 002224292110478
Author(s):  
Xin (Shane) Wang ◽  
Jiaxiu He ◽  
David J. Curry ◽  
Jun Hyun (Joseph) Ryoo
Keyword(s):  
Language Processing ◽  
Contextual Information ◽  
Secondary Data ◽  
Product Category ◽  
Product Attributes ◽  
Product Lines ◽  
Consumer Reviews ◽  
Attribute Hierarchy ◽  
Technical Specifications ◽  
Successive Generations

Sales, product design, and engineering teams benefit immensely from better understanding customer perspectives. How do customers combine a product’s technical specifications (i.e., engineered attributes) to form abstract product benefits (i.e., meta-attributes)? To address this question, the authors use machine learning and natural language processing to develop a methodological framework that extracts a hierarchy of product attributes based on contextual information of how attributes are expressed in consumer reviews. The attribute hierarchy reveals linkages between engineered attributes and meta-attributes within a product category, enabling flexible sentiment analysis that can identify how meta-attributes are received by consumers, and which engineered attributes are main drivers. The framework can guide managers to monitor only portions of review content that are relevant to specific attributes. Moreover, managers can compare products within and between brands, where different names and attribute combinations are often associated with similar benefits. The authors apply the framework to the tablet computer category to generate dashboards and perceptual maps, and provide validations of the attribute hierarchy using both primary and secondary data. Resultant insights allow the exploration of substantive questions, such as how successive generations of iPads were improved by Apple, and why HP and Toshiba discontinued their tablet product lines.

Reconfiguration

2020 ◽  
pp. 379-405
Author(s):  
Howard Hotson
Keyword(s):  
Seventeenth Century ◽  
Intellectual History ◽  
Middle Ages ◽  
Fourth Generation ◽  
Or Education ◽  
Alphabetical Order ◽  
Collective Effort ◽  
Two Generations ◽  
European Intellectual History ◽  
Successive Generations

Alsted and Bisterfeld, Hartlib and Comenius, Welsch and Leibniz all proposed to emend the Encyclopaedia of 1630, and all failed. Contemplating the failure of these attempts opens up the broadest vista attained by this study. The idea of an ‘enkyklios paideia’, a cycle or circle of instruction or education, is an ancient one which gradually took literary shape during the Middle Ages and Renaissance. Three successive generations of reform—led by Agricola, Ramus, and Keckermann—and a fourth generation of collective effort by a whole community generated the most perfect literary manifestation of this idea in Alsted’s Encyclopaedia (section 11.i). For at least two generations after its appearance in 1630, scholars across Europe acknowledged the Encyclopaedia as the leading work of its kind and sought to revise or replace it. During this lengthy period, the connotations of the term ‘encyclopaedia’ shifted from designating a ‘cycle of studies’ to a genre of books which sought to summarize the circle of learning in print (section 11.ii). But with the failure to replace Alsted’s work, the systematically organized, pedagogically orientated, Latin encyclopaedias worthy of the name exploded into innumerable discrete topics which were reorganized in alphabetical order in the various European vernaculars to create a new genre of academic reference works inappropriately labelled ‘(en)cyclopaedias’ first by Chambers in 1728 and then by D’Alembert and Diderot in 1751. The implications of this transformation for the shape of European knowledge were profound. The demise of the age-old tradition culminating in Alsted’s Encyclopaedia can therefore be regarded as a major watershed in European intellectual history created by the simultaneous political, military, confessional, and intellectual crises of the mid-seventeenth century (section 11.iii).

scholarly journals Which cues influence the perceived usefulness and credibility of an online review? A conjoint analysis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ana Isabel Lopes ◽  
Nathalie Dens ◽  
Patrick De Pelsmacker ◽  
Freya De Keyzer
Keyword(s):  
Conjoint Analysis ◽  
Product Category ◽  
Online Reviews ◽  
Perceived Usefulness ◽  
Online Review ◽  
Large Set ◽  
Relative Importance ◽  
Writing Quality ◽  
Content Type ◽  
Argument Strength

PurposeThis study aims to assess the relative importance of the argument strength, argument sidedness, writing quality, number of arguments, rated review usefulness, summary review rating and number of reviews in determining the perceived usefulness and credibility of an online review. Additionally, the authors use insights from the elaboration likelihood model (ELM) to explore the effect of consumers' product category involvement on the cues' relative importance.Design/methodology/approachA conjoint analysis (N = 287) is used to study the relative importance of the seven previously mentioned attributes. A balanced orthogonal design generated eight cards that correspond to individual reviews. Respondents scored all eight cards in a random order for perceived usefulness and credibility.FindingsOverall, argument strength is the most important cue, while summary review rating and the number of reviews are the least important for perceived review usefulness and credibility. The number of arguments is more important for people who are more highly involved with the product, while writing quality and rated review usefulness are relatively more important for the low-involvement group.Originality/valueThis study provides a comprehensive test of how consumers perceive online reviews, as it the first to the authors’ knowledge to simultaneously investigate a large set of cues using conjoint analysis. This method allows for the implicit valuation (utility) of the individual cues, revealing the cues' relative importance, in a setting that comes close to a real-life context. Besides, insights of the ELM are used to understand how the relative importance of cues differs depending on the level of review readers' product category involvement.

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