Dataset Information

Familiarity breeds content: assessing bird species popularity with culturomics.

ABSTRACT: Understanding public perceptions of biodiversity is essential to ensure continued support for conservation efforts. Despite this, insights remain scarce at broader spatial scales, mostly due to a lack of adequate methods for their assessment. The emergence of new technologies with global reach and high levels of participation provide exciting new opportunities to study the public visibility of biodiversity and the factors that drive it. Here, we use a measure of internet saliency to assess the national and international visibility of species within four taxa of Brazilian birds (toucans, hummingbirds, parrots and woodpeckers), and evaluate how much of this visibility can be explained by factors associated with familiarity, aesthetic appeal and conservation interest. Our results strongly indicate that familiarity (human population within the range of a species) is the most important factor driving internet saliency within Brazil, while aesthetic appeal (body size) best explains variation in international saliency. Endemism and conservation status of a species had small, but often negative, effects on either metric of internet saliency. While further studies are needed to evaluate the relationship between internet content and the cultural visibility of different species, our results strongly indicate that internet saliency can be considered as a broad proxy of cultural interest.

SUBMITTER: Correia RA

PROVIDER: S-EPMC4782728 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Familiarity breeds content: assessing bird species popularity with culturomics.

Correia Ricardo A RA Jepson Paul R PR Malhado Ana C M AC Ladle Richard J RJ

PeerJ 20160225

Understanding public perceptions of biodiversity is essential to ensure continued support for conservation efforts. Despite this, insights remain scarce at broader spatial scales, mostly due to a lack of adequate methods for their assessment. The emergence of new technologies with global reach and high levels of participation provide exciting new opportunities to study the public visibility of biodiversity and the factors that drive it. Here, we use a measure of internet saliency to assess the n ...[more]

PMID: 26966663

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Project description:Named Data Networking (NDN) has emerged as a promising network architecture for content delivery in edge infrastructures, primarily due to its name-based routing and integrated in-network caching. Despite these advantages, sub-optimal performance often results from the decentralized decision-making processes of caching devices. This article introduces a paradigm shift by implementing a Software Defined Networking (SDN) controller to optimize the placement of highly popular content in NDN nodes. The optimization process considers critical networking factors, including network congestion, security, topology modification, and flowrules alterations, which are essential for shaping content caching strategies. The article presents a novel content caching framework, Popularity-aware Caching in Popular Programmable NDN nodes (PaCPn). Employing a multi-variant vector autoregression (VAR) model driven by an SDN controller, PaCPn periodically updates content popularity based on time-series data, including 'request rates' and 'past popularity'. It also introduces a controller-driven heuristic algorithm that evaluates the proximity of caching points to consumers, considering factors such as 'distance cost,' 'delivery time,' and the specific 'status of the requested content'. PaCPn utilizes customized DATA named packets to ensure the source stores content with a valid residual freshness period while preventing intermediate nodes from caching it. The experimental results demonstrate significant improvements achieved by the proposed technique PaCPn compared to existing schemes. Specifically, the technique enhances cache hit rates by 20% across various metrics, including cache size, Zipf parameter, and exchanged traffic within edge infrastructure. Moreover, it reduces content retrieval delays by 28%, considering metrics such as cache capacity, the number of consumers, and network throughput. This research advances NDN content caching and offers potential optimizations for edge infrastructures.

Dataset Information

Familiarity breeds content: assessing bird species popularity with culturomics.

Publications

Familiarity breeds content: assessing bird species popularity with culturomics.

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