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ENVIRONMENTAL MONITORING USING
SOCIAL MEDIATHE GREAT BARRIER REEF is an iconic natural attraction that is visited by several million people every year. Many Reef visitors use social media to share their experiences and perceptions. This research examines whether online data can be used for environmental monitoring purposes.
Social media provide large volumes of information at no or little cost, but the data requires considerable cleaning and filtering to extract useful insights.
Different types of analysis are applied to a series of social media data. They rely on domain knowledge to inform machine learning, deep learning, and neural networks to derive meaningful results.
Flickr images: >50 images tagging GBR per day.
Facebook: >25 posts and responses per day across 13 commercial Fb pages.
Weibo: >50 posts mention the GBR per day.
Twitter: >700 tweets globally mention the GBR every day.
Twitter: >1,200 tweets posted from the GBR region per day.
SPATIAL ANALYSIS
KEYWORD ANALYSISIMAGE PROCESSING
Coral Trout
Checkerboard Wrasse
Parrotfish
Sea Turtle
SENTIMENT ANALYSIS
It is possible to use social media data alongside more traditional forms of data collection.
COST OF COLLECTION
DATA QUALITY
DATA VOLUME
VOLUNTARY
EXPERTISE
COLLECTIVE SENSIN
G
(E.G
. TW
ITTER)
HUMAN SENSORS
(E.G
. EYE O
N THE REEF)
CITIZEN SCIENCE
PROFESSIONAL
MONITORING
(SCIENTISTS)
LOW
VERY LARGE
POOR
INVOLUNTARY
NONE
VERY HIGH
SMALL
VERY GOOD
PERSONAL
CONSIDERABLE
Funded by: National Environment Science Program, Tropical Water Quality Hub. Prof Susanne Becken, Prof Bela Stantic, Prof Rod Connolly, Griffith University. For more information contact [email protected]
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Average Twitter sentiment Average Facebook sentiment
SEN
TIM
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