86,834 research outputs found
Understanding User Behavioral Intention to Adopt a Search Engine that Promotes Sustainable Water Management
An increase in users’ online searches, the social concern for an efficient management of resources such as water, and the appearance of more and more digital platforms for sustainable purposes to conduct online searches lead us to reflect more on the users’ behavioral intention with respect to search engines that support sustainable projects like water management projects. Another issue to consider is the factors that determine the adoption of such search engines. In the present study, we aim to identify the factors that determine the intention to adopt a search engine, such as Lilo, that favors sustainable water management. To this end, a model based on the Theory of Planned Behavior (TPB) is proposed. The methodology used is the Structural Equation Modeling (SEM) analysis with the Analysis of Moment Structures (AMOS). The results demonstrate that individuals who intend to use a search engine are influenced by hedonic motivations, which drive their feeling of contentment with the search. Similarly, the success of search engines is found to be closely related to the ability a search engine grants to its users to generate a social or environmental impact, rather than users’ trust in what they do or in their results. However, according to our results, habit is also an important factor that has both a direct and an indirect impact on users’ behavioral intention to adopt different search engines
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The role of search engine optimization in search marketing
This paper examines the impact of search engine optimization (SEO) on the competition between advertisers for organic and sponsored search results. The results show that a positive level of search engine optimization may improve the search engine's ranking quality and thus the satisfaction of its visitors. In the absence of sponsored links, the organic ranking is improved by SEO if and only if the quality provided by a website is sufficiently positively correlated with its valuation for consumers. In the presence of sponsored links, the results are accentuated and hold regardless of the correlation. When sponsored links serve as a second chance to acquire clicks from the search engine, low-quality websites have a reduced incentive to invest in SEO, giving an advantage to their high-quality counterparts. As a result of the high expected quality on the organic side, consumers begin their search with an organic click. Although SEO can improve consumer welfare and the payoff of high-quality sites, we find that the search engine's revenues are typically lower when advertisers spend more on SEO and thus less on sponsored links. Modeling the impact of the minimum bid set by the search engine reveals an inverse U-shaped relationship between the minimum bid and search engine profits, suggesting an optimal minimum bid that is decreasing in the level of SEO activity. © 2013 INFORMS
Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines
Researchers' networks have been subject to active modeling and analysis.
Earlier literature mostly focused on citation or co-authorship networks
reconstructed from annotated scientific publication databases, which have
several limitations. Recently, general-purpose web search engines have also
been utilized to collect information about social networks. Here we
reconstructed, using web search engines, a network representing the relatedness
of researchers to their peers as well as to various research topics.
Relatedness between researchers and research topics was characterized by
visibility boost-increase of a researcher's visibility by focusing on a
particular topic. It was observed that researchers who had high visibility
boosts by the same research topic tended to be close to each other in their
network. We calculated correlations between visibility boosts by research
topics and researchers' interdisciplinarity at individual level (diversity of
topics related to the researcher) and at social level (his/her centrality in
the researchers' network). We found that visibility boosts by certain research
topics were positively correlated with researchers' individual-level
interdisciplinarity despite their negative correlations with the general
popularity of researchers. It was also found that visibility boosts by
network-related topics had positive correlations with researchers' social-level
interdisciplinarity. Research topics' correlations with researchers'
individual- and social-level interdisciplinarities were found to be nearly
independent from each other. These findings suggest that the notion of
"interdisciplinarity" of a researcher should be understood as a
multi-dimensional concept that should be evaluated using multiple assessment
means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On
FilteredWeb: A Framework for the Automated Search-Based Discovery of Blocked URLs
Various methods have been proposed for creating and maintaining lists of
potentially filtered URLs to allow for measurement of ongoing internet
censorship around the world. Whilst testing a known resource for evidence of
filtering can be relatively simple, given appropriate vantage points,
discovering previously unknown filtered web resources remains an open
challenge.
We present a new framework for automating the process of discovering filtered
resources through the use of adaptive queries to well-known search engines. Our
system applies information retrieval algorithms to isolate characteristic
linguistic patterns in known filtered web pages; these are then used as the
basis for web search queries. The results of these queries are then checked for
evidence of filtering, and newly discovered filtered resources are fed back
into the system to detect further filtered content.
Our implementation of this framework, applied to China as a case study, shows
that this approach is demonstrably effective at detecting significant numbers
of previously unknown filtered web pages, making a significant contribution to
the ongoing detection of internet filtering as it develops.
Our tool is currently deployed and has been used to discover 1355 domains
that are poisoned within China as of Feb 2017 - 30 times more than are
contained in the most widely-used public filter list. Of these, 759 are outside
of the Alexa Top 1000 domains list, demonstrating the capability of this
framework to find more obscure filtered content. Further, our initial analysis
of filtered URLs, and the search terms that were used to discover them, gives
further insight into the nature of the content currently being blocked in
China.Comment: To appear in "Network Traffic Measurement and Analysis Conference
2017" (TMA2017
Evaluating the quality of library portals
To investigate ways of demonstrating how portal implementations positively alter user information retrieval behaviour. Design/methodology/approach - An opinion piece reflecting on existing evidence about the nature of portal implementations, which extrapolates trends in user behaviour on the basis of these reflections. Findings - Although portal technologies probably do offer a way for libraries to create information tools that can compete with "one-stop shop" Internet search engines, there are likely difficulties in their pattern of usage which will have to be detected by effective quality measurement techniques. Research limitations/implications - An expression of opinion about the possible pitfalls of using portals to optimise users' information retrieval activity. Practical implications - This opinion piece gives some clear and practical guidelines for the evaluation of the success of library portal implementations. Originality/value - This editorial points out that, because the portal can be defined as a deliberate clone of a typical successful Internet search engine and may be presented to the naïve user in the same terms, the danger is that library portals might also clone the same information habits as Internet search engines, because of their ease of use. In trying to produce a tool that can meet Google on its own terms but with better content, we might reproduce some of the same educational disbenefits as Google: quality information retrieval is not purely a function of content, it is also a function of the user's perceptions and information habits
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