Summarizing Customer Reviews through Aspects and Contexts

2015 ◽  
pp. 241-256 ◽  
Author(s):  
Prakhar Gupta ◽  
Sandeep Kumar ◽  
Kokil Jaidka
Keyword(s):  
Customer Reviews

ROPO Effect in Gender- Generational Characteristics

2020 ◽  
Vol 11 (1) ◽  
pp. 43-43
Author(s):  
Radovan Bačík ◽  
Mária Oleárová ◽  
Martin Rigelský
Keyword(s):  
Association Analysis ◽  
Search Engines ◽  
Product Information ◽  
Customer Behavior ◽  
Internet Research ◽  
The Internet ◽  
Significant Progress ◽  
Customer Reviews ◽  
Online Purchase ◽  
Brick And Mortar

The development of the Internet and the current technologies have contributed to a significant progress in the consumer shopping process. Today, shopping decisions are more intuitive and much easier to make. E-shops, search engines, customer reviews and other similar tools reduce costs of searching for products or product information, thus boosting the habit of searching for information on the Internet - "Research Shopper Phenomenon" (Verhoef et al. 2007). According to Verhoef et al. (2015), this phenomenon leads to a phenomenon where consumers search for product information using one channel (Internet) and then make a purchase through another channel (brick-and-mortar shop). Heinrich and Thalmair (2013) refer to this effect as the "research online, purchase offline" or "ROPO" effect for short. This phenomenon can also be observed in reverse. Keywords: customer behavior, research online – purchase offline, association analysis

Automatic acquisition of customer reviews

2009 ◽  
Vol 29 (3) ◽  
pp. 846-848 ◽  
Author(s):  
Yong-wen HUANG ◽  
Zhong-shi HE ◽  
Xing WU
Keyword(s):  
Customer Reviews ◽  
Automatic Acquisition

scholarly journals SEOpinion: Summarization and Exploration of Opinion from E-Commerce Websites

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 636
Author(s):  
Alhassan Mabrouk ◽  
Rebeca P. Díaz Redondo ◽  
Mohammed Kayed
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Cognitive Processing ◽  
Support Vector ◽  
Processing Capacity ◽  
Customer Reviews ◽  
Aspect Extraction ◽  
Descriptive Information ◽  
Opinion Summarization ◽  
Second Phases

Recently, it has been found that e-commerce (EC) websites provide a large amount of useful information that exceed the human cognitive processing capacity. In order to help customers in comparing alternatives when buying a product, previous research authors have designed opinion summarization systems based on customer reviews. They ignored the template information provided by manufacturers, although its descriptive information has the most useful product characteristics and texts are linguistically correct, unlike reviews. Therefore, this paper proposes a methodology coined as SEOpinion (summarization and exploration of opinions) to summarize aspects and spot opinion(s) regarding them using a combination of template information with customer reviews in two main phases. First, the hierarchical aspect extraction (HAE) phase creates a hierarchy of aspects from the template. Subsequently, the hierarchical aspect-based opinion summarization (HAOS) phase enriches this hierarchy with customers’ opinions to be shown to other potential buyers. To test the feasibility of using deep learning-based BERT techniques with our approach, we created a corpus by gathering information from the top five EC websites for laptops. The experimental results showed that recurrent neural network (RNN) achieved better results (77.4% and 82.6% in terms of F1-measure for the first and second phases, respectively) than the convolutional neural network (CNN) and the support vector machine (SVM) technique.

Profiling Reviewers’ Social Network Strength and Predicting the “Helpfulness” of Online Customer Reviews

2020 ◽  
pp. 101026
Author(s):  
Muhammad Bilal ◽  
Mohsen Marjani ◽  
Ibrahim Abaker Targio Hashem ◽  
Nadia Malik ◽  
Muhammad Ikram Ullah Lali ◽  
...  
Keyword(s):  
Social Network ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Network Strength

Customer Online Feedback with an Identity Versus No Identity: The Influence on Review Comments

2021 ◽  
pp. 109634802098888
Author(s):  
Dan Jin ◽  
Robin B. DiPietro ◽  
Nicholas M. Watanabe
Keyword(s):  
Online Community ◽  
Online Reviews ◽  
Purchasing Behavior ◽  
Mediation Effects ◽  
Driven Systems ◽  
Customer Reviews ◽  
Significant Difference ◽  
Online Feedback ◽  
The Relationship

As customers’ consumption is increasingly dominated by technology-driven systems, online self-verification becomes an important aspect of customers’ online purchasing behavior and plays a significant role in shaping social interactions in the online community. Across two studies, we examine whether online self-verification with an identity versus without an identity will lead to the different quality of online reviews. Study 1 used topic modeling with actual data stripped from Facebook and TripAdvisor customer online review sites and showed no difference between customer reviews underpinned with an identity or without. Likewise, Study 2 used an experimental design and found no significant difference between customer reviews with or without an identity. However, significant mediation effects of social ties and social capital were found when measuring the relationship between online self-verification and customer reviews. The findings build on the literature of user-generated online reviews and have important implications for academics and hospitality practitioners.

Fraud abroad

2019 ◽  
Vol 13 (2) ◽  
pp. 249-275
Author(s):  
Jake David Hoskins ◽  
Ryan Leick
Keyword(s):  
Sharing Economy ◽  
Gdp Per Capita ◽  
Content Type ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Level Of Economic Development ◽  
Per Capita ◽  
Using Data ◽  
Developed Nations

Purpose This study aims to investigate a sharing economy context, where vacation rental units that are owned and operated by individuals throughout the world are rented out through a common website: vrbo.com. It is posited that gross domestic product (GDP) per capita, a common indicator of the level of economic development of a nation, will impact the likelihood that prospective travelers will choose to book accommodations in the sharing economy channel (vs traditional hotels). The role of online customer reviews in this process is investigated as well, building upon a significant body of extant research which shows their level of customer decision influence. Design/methodology/approach An empirical analysis is conducted using data from the website Vacation Rentals By Owner on 1,940 rental listings across 97 countries. Findings GDP per capita serves as risk deterrent to prospective travelers, making the sharing economy an acceptable alternative to traditional hotels for the average traveler. It is also found that the total number of online customer reviews (OCR volume) is a signal of popularity to prospective travelers, while the average star rating of those online customer reviews (OCR valence) is instead a signal of accommodation quality. Originality/value This study adds to a growing agenda of research investigating the effect of online customer reviews on consumer decisions, with a particularly focus on the burgeoning sharing economy. The findings help to explain when the sharing economy may serve as a stronger disruptive threat to incumbent offerings. It also provides the following key insights for managers: sharing economy rental units in developed nations are more successful in driving booking activity, managers should look to promote volume of online customer reviews and positive online customer reviews are particularly influential for sharing economy rental booking rates in less developed nations.

Determining the reliability and validity of online reputation databases for lodging

2017 ◽  
Vol 24 (3) ◽  
pp. 261-274 ◽  
Author(s):  
Manuel Rodríguez Díaz ◽  
Tomás F Espino Rodríguez
Keyword(s):  
Reliability And Validity ◽  
Nonparametric Tests ◽  
Lodging Industry ◽  
Customer Reviews ◽  
Goods And Services ◽  
Strategic Factor ◽  
Customer Evaluations ◽  
New Type ◽  
Marketing Tool ◽  
Online Reputation

Online reputation is a strategic factor in determining the competitiveness and marketing capacity of lodging companies. The influence of online opinions on customers’ decisions is increasing, and, consequently, the online reputation is a new marketing tool to capture clients and reach sales objectives in the lodging industry. In this context, the reliability and validity of customer evaluations available on websites is an essential key to competing in a tourism market influenced by the development of the Internet. The objective of this study is to analyze three of the most important online reputation websites in tourism in order to establish the reliability and validity of the scales used in customer reviews. The results demonstrated that the three websites analyzed fulfill the conventional statistical criteria of reliability and validity. However, a new type of validity is formulated in this study in order to test the capacity of the scales to determine the similarities or differences between tourism goods and services. Nonparametric tests were carried out, demonstrating that although the three websites meet the conventional statistic criteria of reliability and validity, only Booking.com has the capacity to differentiate between destinations.

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