Disentangling ecological and taphonomic signals in ancient food webs

Analyses of ancient food webs reveal important paleoecological processes and responses to a range of perturbations throughout Earth's history, such as climate change. These responses can inform our forecasts of future biotic responses to similar perturbations. However, previous analyses of ancient food webs rarely accounted for key differences between modern and ancient community data, particularly selective loss of soft-bodied taxa during fossilization. To consider how fossilization impacts inferences of ancient community structure, we (1) analyzed node-level attributes to identify correlations between ecological roles and fossilization potential and (2) applied selective information loss procedures to food web data for extant systems. We found that selective loss of soft-bodied organisms has predictable effects on the trophic structure of “artificially fossilized” food webs because these organisms occupy unique, consistent food web positions. Fossilized food webs misleadingly appear less stable (i.e., more prone to trophic cascades), with less predation and an overrepresentation of generalist consumers. We also found that ecological differences between soft- and hard-bodied taxa—indicated by distinct positions in modern food webs—are recorded in an early Eocene web, but not in Cambrian webs. This suggests that ecological differences between the groups have existed for ≥48 Myr. Our results indicate that accounting for soft-bodied taxa is vital for accurate depictions of ancient food webs. However, the consistency of information loss trends across the analyzed food webs means it is possible to predict how the selective loss of soft-bodied taxa affects food web metrics, which can permit better modeling of ancient communities.

Digital Marketing Best Practices for Management in Tourism Destinations

This work fills a gap that has existed up to now, proposing a series of specific indicators that serve as a manual of good digital marketing practices for the promotion of tourism destinations. According to the proposed model, the variables to take into account are those related to web metrics, SEO positioning, and social networks. Likewise, the indicators and metrics proposed in the tourism destination Malaga (Spain) are applied. In this way, the model can serve as a guide for the managing institutions of tourism destinations that wish to measure the results of their efforts. This analysis facilitates the identification of the strengths of the strategy followed, as well as those that need to be improved. It can also be used to verify the positioning of tourism destinations with respect to their competitors.

Digital Marketing Best Practices for Management in Tourist Destinations

This work fills a gap that has existed up to now, proposing a series of specific indicators that serve as a manual of good digital marketing practices for the promotion of tourist destinations. According to the proposed model, the variables to take into account are those related to web metrics, SEO positioning, and social networks. Likewise, the indicators and metrics proposed in the tourist destination Malaga (Spain) are applied. In this way, the model can serve as a guide for the managing institutions of tourist destinations that wish to measure the results of their efforts. This analysis facilitates the identification of the strengths of the strategy followed, as well as those that need to be improved. It can also be used to verify the positioning of tourist destinations with respect to their competitors.

Increasing Participation in Large-Scale Virtual Environments

The proliferation of media-rich social networking services has changed the way people use information society and audio-visual media services. Existing theories of cognition in human-computer interaction have limitations in dealing with the unique problems that exist in contemporary virtual environments. The presence of significant numbers of people using these at the same time causes behavioural issues not previously envisaged at the time of multi-user domains (MUDs) or the first massively-multiplayer online role-playing games. To understand such large-scale virtual environments, this chapter makes use of data generated from questionnaires, usability testing, and social and web metrics to assess the relevance of ecological cognition theory for the current age. Through making use of a biometric measure called ‘knol', the chapter suggests a new framework for measuring emotion and cognition in these and future environments.

Application of web Metrics and Text Mining on the IRCTC Portal

The Indian railways, a historical inheritance, the 4th largest railway network in the world by size, is an important force in our economy. The digitalization has enabled the customer to get the railway services on their finger tip. IRCTC, the subsidiary of the Indian railway offers variety of service like catering, tourism and the online ticket operation. As technology advancement is taking place, but the IRCTC has been widely criticized for many lacunas in meeting the customer needs and preference. So the study focuses on how Indian Railway needs to revamp the website to make it more contributing to customer expectations. An analysis of customer reviews, revealed that the customers experience many problems while using the IRCTC website to make their choice about the type of travel, coach preference, seat preferences, age group, payment gateways, time and date of travel, etc. The study attempts to find out the user-friendliness of IRCTC website from the point of view of the customers using four identified dimensions or variables. The analysis was done using various web metrics and a text-mining based on the customer reviews. It helped to know about the clicks rates pattern, visit rate, the various activities performed by the customer, time spent, type of device used, keywords used etc. The result shows that majority users have stated negatively towards the features and usability of the website. Based on the analysis of the study a brief summary of findings have been made and a meaningful conclusion have been obtained.

Reflecting on the Success of Open Data

Despite the high level of interest in open data, little research has evaluated how municipal government evaluates the success of their open data programs. This research presents results from interviews with eight Canadian municipal governments that point to two approaches to evaluation: internal and external. Internal evaluation looks for use within the data generating government, and for support from management and council. External evaluation tracks use by external entities, including citizens, private sector, or other government agencies. Three findings of this work provide guidance for the development of open data evaluation metrics. First, approaches to tracking can be both passive, via web metrics, and active, via outreach activities to users. Second, value of open data must be broadly defined, and extend beyond economic valuations. Lastly, internal support from management or council and the contributions of many organization employees towards the production of open data are important forms of self-evaluation of open data programs.