Conservation implications and opportunities of mining activities for terrestrial mammal habitat

Mining companies increasingly commit to a net positive impact on biodiversity. However, assessing the industry's progress toward achieving this goal is limited by knowledge of current mining threats to biodiversity and the relevant opportunities available for them to improve conservation outcomes. Here, we investigate the global exposure of terrestrial mammal habitat to mining activities, revealing the 136 species with > 30% of their habitat within 10 km of a mining property or exploration site. One third (n = 42) of these species are already threatened with extinction according to the International Union for Conservation of Nature (IUCN), suggesting projected increased demand for minerals may push some species beyond critical thresholds. Moreover, 28% (n = 33) of species are Data Deficient, illustrating tangible ways for industry to fill current knowledge gaps. However, large discrepancies between our results and the species currently listed as threatened by mining in the IUCN Red List, suggest other species may be at risk and that conservation tools and analyses based on these data may underestimate the benefits of averting such threats. We recommend ways to better capture mining threats to species within IUCN Red List assessments and discuss how these changes could improve conservation outcomes in mineral-rich areas

Semantic Sentiment Analysis of Twitter Data

Internet and the proliferation of smart mobile devices have changed the way information is created, shared, and spreads, e.g., microblogs such as Twitter, weblogs such as LiveJournal, social networks such as Facebook, and instant messengers such as Skype and WhatsApp are now commonly used to share thoughts and opinions about anything in the surrounding world. This has resulted in the proliferation of social media content, thus creating new opportunities to study public opinion at a scale that was never possible before. Naturally, this abundance of data has quickly attracted business and research interest from various fields including marketing, political science, and social studies, among many others, which are interested in questions like these: Do people like the new Apple Watch? Do Americans support ObamaCare? How do Scottish feel about the Brexit? Answering these questions requires studying the sentiment of opinions people express in social media, which has given rise to the fast growth of the field of sentiment analysis in social media, with Twitter being especially popular for research due to its scale, representativeness, variety of topics discussed, as well as ease of public access to its messages. Here we present an overview of work on sentiment analysis on Twitter.Comment: Microblog sentiment analysis; Twitter opinion mining; In the Encyclopedia on Social Network Analysis and Mining (ESNAM), Second edition. 201

Virtual Astronomy, Information Technology, and the New Scientific Methodology

All sciences, including astronomy, are now entering the era of information abundance. The exponentially increasing volume and complexity of modern data sets promises to transform the scientific practice, but also poses a number of common technological challenges. The Virtual Observatory concept is the astronomical community's response to these challenges: it aims to harness the progress in information technology in the service of astronomy, and at the same time provide a valuable testbed for information technology and applied computer science. Challenges broadly fall into two categories: data handling (or "data farming"), including issues such as archives, intelligent storage, databases, interoperability, fast networks, etc., and data mining, data understanding, and knowledge discovery, which include issues such as automated clustering and classification, multivariate correlation searches, pattern recognition, visualization in highly hyperdimensional parameter spaces, etc., as well as various applications of machine learning in these contexts. Such techniques are forming a methodological foundation for science with massive and complex data sets in general, and are likely to have a much broather impact on the modern society, commerce, information economy, security, etc. There is a powerful emerging synergy between the computationally enabled science and the science-driven computing, which will drive the progress in science, scholarship, and many other venues in the 21st century

Mining social network data for personalisation and privacy concerns: A case study of Facebook’s Beacon

This is the post-print version of the final published paper that is available from the link below.The popular success of online social networking sites (SNS) such as Facebook is a hugely tempting resource of data mining for businesses engaged in personalised marketing. The use of personal information, willingly shared between online friends' networks intuitively appears to be a natural extension of current advertising strategies such as word-of-mouth and viral marketing. However, the use of SNS data for personalised marketing has provoked outrage amongst SNS users and radically highlighted the issue of privacy concern. This paper inverts the traditional approach to personalisation by conceptualising the limits of data mining in social networks using privacy concern as the guide. A qualitative investigation of 95 blogs containing 568 comments was collected during the failed launch of Beacon, a third party marketing initiative by Facebook. Thematic analysis resulted in the development of taxonomy of privacy concerns which offers a concrete means for online businesses to better understand SNS business landscape - especially with regard to the limits of the use and acceptance of personalised marketing in social networks

Conference News: Social Policy in Mineral-Rich Countries

This document is part of a digital collection provided by the Martin P. Catherwood Library, ILR School, Cornell University, pertaining to the effects of globalization on the workplace worldwide. Special emphasis is placed on labor rights, working conditions, labor market changes, and union organizing.UNRISD_SocialPolicyInMineralRichCountries.pdf: 189 downloads, before Oct. 1, 2020

Animal community dynamics at senescent and active vents at the 9° N East Pacific Rise after a volcanic eruption

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Gollner, S., Govenar, B., Arbizu, P. M., Mullineaux, L. S., Mills, S., Le Bris, N., Weinbauer, M., Shank, T. M., & Bright, M. Animal community dynamics at senescent and active vents at the 9° N East Pacific Rise after a volcanic eruption. Frontiers in Marine Science, 6, (2020): 832, doi:10.3389/fmars.2019.00832.In 2005/2006, a major volcanic eruption buried faunal communities over a large area of the 9°N East Pacific Rise (EPR) vent field. In late 2006, we initiated colonization studies at several types of post eruption vent communities including those that either survived the eruption, re-established after the eruption, or arisen at new sites. Some of these vents were active whereas others appeared senescent. Although the spatial scale of non-paved (surviving) vent communities was small (several m2 compared to several km2 of total paved area), the remnant individuals at surviving active and senescent vent sites may be important for recolonization. A total of 46 meio- and macrofauna species were encountered at non-paved areas with 33 of those species detected were also present at new sites in 2006. The animals living at non-paved areas represent refuge populations that could act as source populations for new vent sites directly after disturbance. Remnants may be especially important for the meiofauna, where many taxa have limited or no larval dispersal. Meiofauna may reach new vent sites predominantly via migration from local refuge areas, where a reproductive and abundant meiofauna is thriving. These findings are important to consider in any potential future deep-sea mining scenario at deep-sea hydrothermal vents. Within our 4-year study period, we regularly observed vent habitats with tubeworm assemblages that became senescent and died, as vent fluid emissions locally stopped at patches within active vent sites. Senescent vents harbored a species rich mix of typical vent species as well as rare yet undescribed species. The senescent vents contributed significantly to diversity at the 9°N EPR with 55 macrofaunal species (11 singletons) and 74 meiofaunal species (19 singletons). Of these 129 species associated with senescent vents, 60 have not been reported from active vents. Tubeworms and other vent megafauna not only act as foundation species when alive but provide habitat also when dead, sustaining abundant and diverse small sized fauna.We received funding from the Austrian FWF (GrantP20190-B17; MB), the U.S. National Science Foundation (OCE-0424953; to LM, D. McGillicuddy, A. Thurnherr, J. Ledwell, and W. Lavelle; and OCE-1356738 to LM), and the European Union Seventh Framework Programme (FP7/2007-2013) under the MIDAS project, Grant Agreement No. 603418. Ifremer and CNRS (France) supported NL cruise participation and sensor developments. BG was supported by a postdoctoral fellowship from the Deep Ocean Exploration Institute at WHOI (United States). TS was supported by the U.S. National Science Foundation (OCE-0327261 to TS and OCE-0937395 to TS and BG)

Datamining for Web-Enabled Electronic Business Applications

Web-Enabled Electronic Business is generating massive amount of data on customer purchases, browsing patterns, usage times and preferences at an increasing rate. Data mining techniques can be applied to all the data being collected for obtaining useful information. This chapter attempts to present issues associated with data mining for web-enabled electronic-business