Factors Affecting Users’ Mental Models of a Web Search Engine: A Case Study

2013 ◽  
Author(s):  
Li Ping ◽  
Jamshid Beheshti.
Keyword(s):  
Mental Models ◽  
Doctoral Students ◽  
Search Engine ◽  
Web Search ◽  
Search Performance ◽  
User Group ◽  
Factors Affecting ◽  
Web Search Engine ◽  
Collecte De Données

Focusing on doctoral students as a specific user group, for a case study, this research investigates factors that might affect users’ mental models of a Web search engine measured in the dimension of completeness, and subsequently on their search performance. Data collection techniques include interview, observation and four standard tests.Se basant sur les étudiants au doctorat comme groupe spécifique d’utilisateurs pour réaliser une étude de cas, cette recherche examine les facteurs pouvant affecter les modèles mentaux des utilisateurs d’un moteur de recherche web, mesurés en termes d’exhaustivité, et subséquemment en termes de performance de recherche. Les techniques de collecte de données incluent l’entrevue, l’observation et quatre tests standardisés. 

Doctoral Students’ Mental Models of a Web Search Engine

2013 ◽  
Author(s):  
Ping Li ◽  
Jamshid Beheshti
Keyword(s):  
Pilot Study ◽  
Mental Models ◽  
Doctoral Students ◽  
Search Engine ◽  
Mental Model ◽  
Web Search ◽  
Model Completeness ◽  
Web Search Engine

This paper reports on the first stage of a research on doctoral students’ mental models of a Web search engine and factors that may affect their mental models. A modified version of a mental model completeness scale was developed and tested in a pilot study in Web search engine context.Cet article présente le premier stade d'une recherche sur les modèles mentaux des étudiants doctoraux avec un moteur de recherche Web et les facteurs qui peuvent les affecter. Une version modifiée d’une échelle de la perfection du modèle mental a été développée et examinée dans le contexte d’une étude préliminaire effectuée avec un moteur de recherche Web. 

Mental Models and Information Retrieval: What Can Search Queries Tell Us?

2013 ◽  
Author(s):  
Haidar Moukdad ◽  
Andrew Large
Keyword(s):  
Information Retrieval ◽  
Mental Models ◽  
Search Engine ◽  
Mental Model ◽  
Web Search ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Search Queries ◽  
Web Search Engine ◽  
Advanced Search

When information seekers use an information retrieval system their strategy is based, at least in part, on the mental model they have constructed about this environment. A random sample was gathered of more than 2000 actual search queries submitted by users to one web search engine. WebCrawler, in two separate capture sessions. The results suggest that a high proportion of users do not employ advanced search features...

scholarly journals Gig Economy and the Future of Work: A Fiverr.com Case Study

2018 ◽  
Vol 4 (2) ◽  
pp. 281 ◽  
Author(s):  
Daryl D. Green ◽  
Jack McCann ◽  
Thao Vu ◽  
Nancy Lopez ◽  
Samuel Ouattara ◽  
...  
Keyword(s):  
Search Engine ◽  
Web Search ◽  
Swot Analysis ◽  
New Economy ◽  
The Internet ◽  
Global Marketplace ◽  
The Past ◽  
Web Search Engine ◽  
Gig Economy

Twenty years ago, Google became the first web search engine to help people find things on the Internet. Today, people use Google to help organize the infinite data found on the Internet and to find things such as logo designs, business copywriting, promotional videos, or even information on astrology. With the technological advancements of the past decade, these services are found not only at the local marketplace but also in the global marketplace — a workplace of freelancing challenges in a gig economy. The term “gig economy” is clarified in a detailed analysis of one largest freelance websites, Fiverr.com. This case study starts with valuable reviews from a variety of authors about this new economy. Fiverr is the target for analysis regarding growth of the gig economy, and with that growth, there are also opportunities for Fiverr’s competitors. This study includes a PESTLE analysis, Competitive analysis, as well as SWOT analysis of Fiverr and its competition. The results are significant, because the conclusions can better assist scholars and practitioners about how to better utilize freelance services from firms such as Fiverr, found in the gig economy.

scholarly journals Architecture of a grid-enabled Web search engine

2007 ◽  
Vol 43 (3) ◽  
pp. 609-623 ◽  
Author(s):  
B. Barla Cambazoglu ◽  
Evren Karaca ◽  
Tayfun Kucukyilmaz ◽  
Ata Turk ◽  
Cevdet Aykanat
Keyword(s):  
Search Engine ◽  
Web Search ◽  
Web Search Engine
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