/pdf/a-break-in-the-clouds-towards-a-cloud-definition-svovsw1r5a.pdf

A Break in the Clouds: Towards a Cloud Definition

[서평]「Component Software」 - Beyond Object-Oriented Programming -

Now days, E-commerce systems have become extremely important. Large numbers of customers are choosing online shopping because of its convenience, reliability, and cost. Client generated information and especially item reviews are significant sources of data for consumers to make informed buy choices and for makers to keep track of customer’s opinions. It is difficult for customers to make purchasing decisions based on only pictures and short product descriptions. On the other hand, mining product reviews has become a hot research topic and prior researches are mostly based on pre-specified product features to analyse the opinions. Natural Language Processing (NLP) techniques such as NLTK for Python can be applied to raw customer reviews and keywords can be extracted. This paper presents a survey on the techniques used for designing software to mine opinion features in reviews. Elven IEEE papers are selected and a comparison is made between them. These papers are representative of the significant improvements in opinion mining in the past decade.

Mining Opinion Features in Customer Reviews.

Predicting the antecedents of trust in social commerce – A hybrid structural equation modeling with neural network approach

This study investigated the impact of online product reviews on consumers purchasing decisions by using eye-tracking. The research methodology involved (i) development of a conceptual framework of online product review and purchasing intention through the moderation role of gender and visual attention in comments, and (ii) empirical investigation into the region of interest (ROI) analysis of consumers fixation during the purchase decision process and behavioral analysis. The results showed that consumers’ attention to negative comments was significantly greater than that to positive comments, especially for female consumers. Furthermore, the study identified a significant correlation between the visual browsing behavior of consumers and their purchase intention. It also found that consumers were not able to identify false comments. The current study provides a deep understanding of the underlying mechanism of how online reviews influence shopping behavior, reveals the effect of gender on this effect for the first time and explains it from the perspective of attentional bias, which is essential for the theory of online consumer behavior. Specifically, the different effects of consumers’ attention to negative comments seem to be moderated through gender with female consumers’ attention to negative comments being significantly greater than to positive ones. These findings suggest that practitioners need to pay particular attention to negative comments and resolve them promptly through the customization of product/service information, taking into consideration consumer characteristics, including gender.

https://www.frontiersin.org/articles/10.3389/fpsyg.2022.865702/pdf

The Impact of Online Reviews on Consumers’ Purchasing Decisions: Evidence From an Eye-Tracking Study

Product reviews and ratings are popular tools to support buying decisions of consumers. These tools are also valuable for online retailers, who use rating systems in order to build trust and reputation in the online market. Many online shops offer quantitative ratings, textual reviews or a combination of both. This paper examines the acceptance and usage of ratings and reviews in the context of e-commerce transactions. A survey among 104 German online shoppers was conducted to examine how consumer reviews and rat- ings are used to support buying decisions. The survey shows that reviews and ratings are an important source of information for consumers. However, qualitative feedback from the survey indicates that the perceived helpfulness of rating systems varies. Especially the comparison of user reviews is a very time consuming process for the customer, because of the unstructured nature of textual user reviews. In this paper we summarize similar problems and show corresponding examples to them. This will give new insight for future research in the area of user ratings and reviews.

/pdf/importance-of-online-product-reviews-from-a-consumer-s-4rw1pr1zpc.pdf

Importance of Online Product Reviews from a Consumer's Perspective

Customers in electronic commerce (e-commerce) are shifting more and more from content consumers to content producers. Social media features (like customer reviews) allow and encourage user interaction in online stores. An interesting question is, which social media features are actually provided by online stores to support user interaction. We contribute knowledge to this question, by studying the social media features of the 115 highest-grossing German B2C-online stores from the years 2010 and 2011. We categorize the results of the observational study into the seven building blocks of social media to understand what areas of social media are used the most in these online stores. The results of our study show, that the average online store implements about five social media features and that the majority of the features are placed on product pages. The most common features were customer reviews and ratings and the sharing and liking of product details.

/pdf/an-empirical-study-on-the-usage-of-social-media-in-german-5dnbuwbahw.pdf

An empirical study on the usage of social media in german b2c-online stores

Collaborative tagging is a popular way to organize content. But sometimes it is also used as a way to express opinions, which is normally done through rating- or text review systems. This paper will demonstrate that there is a gap between rating- and text review systems, that limits the ability of users to find the desired item. A novel concept based on collaborative tagging is presented, which is designed to bridge this gap. This concept, named Rated Tags, uses a hybrid approach to combine tagging-, rating- and review functionality. A key element of Rated Tags is the combination of a traditional user generated tag and a 5-star rating scale. Such a tag is called rated tag. We will discuss the design and the challenges of Rated Tags in detail and demonstrate its application based on a prototype. Furthermore we will show that similar related works suffer from an ambiguity problem, which was avoided in Rated Tags.

Rated Tags: Adding Rating Capability to Collaborative Tagging

In this paper, we present an empirical study that conducts the impact of Rated Tags on customers' decision making process in online stores. A Rated Tag is a combination of a user-generated tag and a 5-star rating scale. The Rated Tags system aims to support consumers' decisions and therefore falls into the category of interactive decision aids. The questions answered in this paper are whether Rated Tags can increase the decision making quality and decrease the decision effort of consumers. For this purpose, we have extracted 100 real customer reviews from amazon.de, which were assigned Rated Tags. The customer reviews and Rated Tags were used as a basis for the decision making process of our participants. The results of the study are promising. Participants of the Rated Tags group had an increased decision quality and a decreased decision making effort compared to the participants of the control group.

Supporting customers' decision making with Rated Tags

/pdf/rated-tags-as-a-service-konzept-und-evaluierung-3zccddev1i.pdf

Rated Tags as a Service - Konzept und Evaluierung

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Daniel Kailer

Author Tools

Chat about Author