scholarly journals Google Scholar and meta descriptions : does adding abstracts to a search engine results page aid in undergraduate document triage efficiency?

2015 ◽  
Author(s):  
◽  
Nathan John Lowrance

By focusing on the point where the document triage process interacts with a search engine results page (SERP), this experiment extends our knowledge about both SERP design and document triage behavior. Prior SERP work has shown that longer meta descriptions in SERPs improve people's ability to answer information based questions, while document triage research has shown the importance of abstracts in making relevancy decisions. Using eye tracking equipment this work employed a repeated measure within factors experimental design method replacing the existing Google Scholar (GS) SERP meta descriptions with the abstracts of the corresponding retrieved articles. Undergraduate freshmen participants were asked to use two different GS SERPs, one with a control design and one with the experimental design and determine which resources are relevant to their assigned research task. The findings show that the participants changed how long they looked at the expanded meta description, while noticeably reducing how long they gazed at other parts of the page supporting other research findings. The addition of abstracts changed user behavior by reducing how often they made surrogate level document transitions, but did not change how often they sought out full-text documents, supporting the principle of least effort. The addition of abstracts did not contribute to changes in total time on task or participant's relevancy accuracy. This study's findings conflict with other work that found that longer meta descriptions corresponded with a reduction in total task time and an improvement in accuracy for informational tasks. Further research is needed to determine if this conflict was due to task differences or if the document triage task was not challenging enough.

2020 ◽  
Vol 4 (2) ◽  
pp. 5 ◽  
Author(s):  
Ioannis C. Drivas ◽  
Damianos P. Sakas ◽  
Georgios A. Giannakopoulos ◽  
Daphne Kyriaki-Manessi

In the Big Data era, search engine optimization deals with the encapsulation of datasets that are related to website performance in terms of architecture, content curation, and user behavior, with the purpose to convert them into actionable insights and improve visibility and findability on the Web. In this respect, big data analytics expands the opportunities for developing new methodological frameworks that are composed of valid, reliable, and consistent analytics that are practically useful to develop well-informed strategies for organic traffic optimization. In this paper, a novel methodology is implemented in order to increase organic search engine visits based on the impact of multiple SEO factors. In order to achieve this purpose, the authors examined 171 cultural heritage websites and their retrieved data analytics about their performance and user experience inside them. Massive amounts of Web-based collections are included and presented by cultural heritage organizations through their websites. Subsequently, users interact with these collections, producing behavioral analytics in a variety of different data types that come from multiple devices, with high velocity, in large volumes. Nevertheless, prior research efforts indicate that these massive cultural collections are difficult to browse while expressing low visibility and findability in the semantic Web era. Against this backdrop, this paper proposes the computational development of a search engine optimization (SEO) strategy that utilizes the generated big cultural data analytics and improves the visibility of cultural heritage websites. One step further, the statistical results of the study are integrated into a predictive model that is composed of two stages. First, a fuzzy cognitive mapping process is generated as an aggregated macro-level descriptive model. Secondly, a micro-level data-driven agent-based model follows up. The purpose of the model is to predict the most effective combinations of factors that achieve enhanced visibility and organic traffic on cultural heritage organizations’ websites. To this end, the study contributes to the knowledge expansion of researchers and practitioners in the big cultural analytics sector with the purpose to implement potential strategies for greater visibility and findability of cultural collections on the Web.


2005 ◽  
Vol 42 (1) ◽  
pp. 90-98
Author(s):  
Hiroko Miyaji ◽  
Hirofumi Sakurai ◽  
Masayuki Kikawada ◽  
Katsuhiko Yamaguchi ◽  
Akihiro Kimura ◽  
...  

2014 ◽  
Vol 18 (5) ◽  
pp. 1714-1715
Author(s):  
Li-Li Wu ◽  
Ting-Ting Cheng ◽  
Chuan Xu ◽  
Ting Chen

The parameters of the dual slot die in an industrial melt blowing equipment are designed optimally using the orthogonal experimental design method. The air flow fields of different die parameters are simulated. Effects of the die parameters are analyzed using variance analysis. The results show that the inset distance and slot width have significant effects on the air flow field while effect of the slot angle is unremarkable.


Author(s):  
Muhammad Arif Mustaqim ◽  

The objectives of this research were to examine the Influence of Principal Leadership toward Teacher Performance. This research consists of independent variables (Principal Leadership) and the dependent variable (Teacher performance). This research was used a qualitative descriptive method by Literature Review. Data collected by a search engine, google scholar, to search the articles with keywords. Principal’s leadership and teacher performance. Based on the results of the literature review we found that there is the influence of principal leadership toward teacher performance across various countries, in general, it can be concluded that there is the influence of principal leadership toward teacher performance.


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