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A cutting-edge Tropical Water Quality Hub \u2018Big Data\u2019 project has developed new ways of integrating and analysing large amounts of information from social media and other sources to give new insights into the tourist public\u2019s perception of the Great Barrier Reef.<\/p>\n
Dr Susanne Becken from Griffith University<\/a> and her Tropical Water Quality Hub project<\/a> team are using cutting-edge computing methods, including machine learning, to analyse a huge amount of posts on Twitter, Facebook and Chinese social media service Weibo sent from within a geographic \u2018bounding box\u2019 covering the Great Barrier Reef.<\/p>\n The system detects certain keywords relating to the poster\u2019s perception of quality of coral, wildlife and other indicators on the Reef.<\/p>\n It also sources data from other repositories including Eye On The Reef<\/a> and CoralWatch<\/a>.<\/p>\n Collating and analysing the vast amount of information involved is a challenge, but since the project began in 2016 the team has improved their data-sifting capabilities, including the introduction of a new technique called \u2018BoostIso\u2019 that speeds up results by reducing the amount of duplicated calculations.<\/p>\n Using these techniques and others, Dr Becken and her team analysed the posts and revealed some interesting insights into the attitude of Great Barrier Reef tourists.<\/p>\n These social media posts form part of a global conversation on the health and future of the Great Barrier Reef, framed by the back-to-back mass bleaching events in 2016 and 2017. A significant proportion of this media coverage gave a very bleak outlook for the GBR\u2019s current and future condition, with one outlet controversially proclaiming the GBR to \u2018already be dead\u2019.<\/a><\/p>\n However, despite these grim descriptors, Dr Becken\u2019s analysis reveals that most social media posts made from within the region reflect a positive experience on the Great Barrier Reef.<\/p>\n \u201cBleaching was not mentioned by local tweets that much at all, with only 90 out of 1500 tweets containing references to it,\u201d Dr Becken said.<\/p>\n \u201cPeople who are there on the Reef are quite happy and they don\u2019t seem to post about bleaching.\u201d<\/p>\n \u201cFacebook posts, with their higher wordcount, tend to start conversation threads about environmental health, while posts from Twitter are shorter and often have more negative content.\u201d<\/p>\n The innovative social science project was a controversial choice for investment through the NESP Tropical Water Quality Hub, but despite only starting this year, it has already gained prominent media coverage in The Conversation<\/a> and worldwide media interest.<\/p>\n It also links to other NESP TWQ Hub projects including one scoring aesthetic values on the Great Barrier Reef<\/a> by analysing imagery posted on social media.<\/p>\n \u201cThis project is using over 12,000 images from Flickr, 20 per cent of which had exact location coordinates,\u201d Dr Becken said.<\/p>\n \u201cThe algorithm in use here can recognisably recognise 10 species like sea turtles, coral trout and others, and we are looking to access Instagram feeds as well.\u201d<\/p>\n While these immediate insights are interesting, the Big Data approach has much potential as a monitoring tool in the future.<\/p>\n \u201cThe way we see it, social media analysis can fall on the other end of the spectrum to a traditional professional analysis, and it can be approached as a hybrid system.<\/p>\n \u201cWe are also investigating the possibility of integration with the eAtlas<\/a>. If stakeholders agree we could bring these systems together.<\/p>\n \u201cThe way we see it, analysing text posts will be good for revealing human information like attitudes toward reef conditions, while analysing images could be used for environmental monitoring.<\/p>\n \u201cThis approach has a wide range of possible applications in environmental monitoring, not just on the Great Barrier Reef but elsewhere.\u201d<\/p>\n <\/p>\n <\/p>\n A cutting-edge Tropical Water Quality Hub \u2018Big Data\u2019 project has developed new ways of integrating and analysing large amounts of information from social media and other sources to give new … Read More<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":3765,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"om_disable_all_campaigns":false,"footnotes":""},"class_list":["post-3773","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/nesptropical.edu.au\/index.php\/wp-json\/wp\/v2\/pages\/3773","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nesptropical.edu.au\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/nesptropical.edu.au\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/nesptropical.edu.au\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/nesptropical.edu.au\/index.php\/wp-json\/wp\/v2\/comments?post=3773"}],"version-history":[{"count":0,"href":"https:\/\/nesptropical.edu.au\/index.php\/wp-json\/wp\/v2\/pages\/3773\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/nesptropical.edu.au\/index.php\/wp-json\/wp\/v2\/pages\/3765"}],"wp:attachment":[{"href":"https:\/\/nesptropical.edu.au\/index.php\/wp-json\/wp\/v2\/media?parent=3773"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"](\"http:\/\/nesptropical.edu.au\/wp-content\/uploads\/2017\/10\/Software-Chart.jpg\")
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Back to the October 2017 e-Newsletter contents<\/strong><\/a><\/h5>\n","protected":false},"excerpt":{"rendered":"