Acknowledgment to Country I would like to acknowledge the traditional custodians of the land on which we are meeting. I would also like to pay respects to elders past, present, and emerging. 1
Public Participation in the Digital Age: Social Media Reactions about an Iconic Species Montannia Chabau-Gibson Prof. Catherine Pickering In collaboration with: 2
INTRODUCTION 3
TOPIC DEFINITIONS ❖ Social Media: Websites and applications that enable users to create and share content ❖ Iconic Species: Flora or fauna that are important to cultural identity (e.g. Koala, Lion) ❖ Crowd source data: Building data sets with contribution from large sets of people ❖ Digital age: Time period starting in 1970-80s of the advancement of technology ❖ Application Program Interface (API): The creation of an application that accesses data 4
SOCIAL MEDIA AS A DATA BASE ❖ Social media – large participants ❖ Enormous amount of user created content ❖ Communication amongst people independently ❖ Virtual communities, virtual landscapes Active social media users per month (Millions) Source: (Statistica 2019) 6
SOCIAL MEDIA DATA CONSIDERATIONS 1. What are the current data/databases that already exist? 2. What are their disadvantages? 3. What data can be accessed and how? 4. What are the privacy/ethics/property rights of the data? 5. How can social media data benefit additional databases? 6. How to display/analyse the data? BENEFITS LIMITATIONS ❖ Large amounts of data generated daily ❖ Data representative of peoples opinions ❖ Can access a different audience varying in age ❖ Over representation of views and location ❖ Only limited groups using social media ❖ Social media data can have geo-data ❖ Coders interpretation of words ❖ Can access metadata (spatial and temporal) ❖ Whether sufficient data for the topic ❖ Can also do textual and image content analysis investigated is available 7
WHAT CAN WE LEARN? TWITTER GOOGLE TRENDS ❖ Online news and social networking site – ❖ Website that analyses comparative communication occurs via tweets (Twitter keyword research (Google Trends 2019) 2019) ❖ Google Trends: 1.17 Billion People utilise ❖ Twitter: accumulates 4% of the international as a search engine – 40,000 searches on social media activity > 275 million google each second registered tweeters ❖ Interest by region and country ❖ Information on the sociocultural dimensions - ❖ Trending terms and topics spatial and temporal data ❖ Twitter Storms: Folksonomy research 8
THESIS RESEARCH 8
BACKGROUND RATIONALE MERMAID BEACH, CITY OF GOLD COAST URBAN GROWTH ❖ Public participation in planning practice 1939 Biodiversity ❖ 55% of the world population living in cities, expected to Social Habitat increase to 68% in 2050 (United Nations 2018) Licence loss THESIS Social ❖ Pressure for urban environments to change Planning TOPIC Media 2019 Community Traditional ❖ The issue of habitat loss from expansion (Evans et al. 2011) Involvement Methods ❖ Affects biodiversity and Iconic species (Koala) Public Participation 9
RESEARCH QUESTION How can we use social media research to make better planning decisions? SUB RESEARCH QUESTIONS RESEARCH AIMS 1. Can social media research contribute to What insights can be gained from ❖ policy making in councils? analysing social media data 2. How does public participation function in Exploring and reflecting on the ❖ the digital age? process of developing research questions in a collaborating process 3. What makes an iconic species, and how can this influence a locations image? To discover the influence of iconic ❖ species through the use of user 4. How does the online public associate created textual content meaning to Koala, Gold Coast? 10
TWITTER DATA RESULTS Shopping Twitter Data Pull: Search term “Koala” & “Gold Coast” ❖ Duration of 1 st Aug 2018 - 27 th Nov 2018 ❖ 1298 Tweets in total ❖ 982 Retweets 11
TWITTER DATA SEARCH STORMS Scored Rank 100 150 200 250 50 0 (blank) 1-Aug 2 3-Aug 5-Aug 7-Aug 9-Aug 13-Aug 15-Aug Twitter Data Koala search terms over the duration of 17-Aug 5 4 20-Aug 23-Aug 25-Aug 27-Aug 1st Aug 2018 – 27 th Nov 2018 4 29-Aug 31-Aug 2-Sep 4-Sep Date 6-Sep 8-Sep 11-Sep 13-Sep 20-Sep 17-Oct 26-Oct 29-Oct 3 1-Nov 5-Nov 7-Nov 9-Nov Hashtags used: #Koala #GoldCoast 14-Nov 16-Nov 19-Nov 23-Nov 25-Nov 1 27-Nov 12 1 2 3
NUMBER OF TWEETS PER DAY Hashtags used: #Koala #GoldCoast Twitter Data - Most Popular Days Twitter Data - User Location Distribution 350 450 400 300 350 Tweet Score Rank 250 300 200 Values 250 200 150 150 100 100 50 50 0 0 1 2 3 4 5 6 7 Local Australia International Locations Weekdays 14 Source: (Chabau-Gibson 2018)
NUMBER OF TWEETS PER DAY Hashtags used: #Koala #GoldCoast Twitter Data – Most Popular Months Twitter Data - Most Popular Times 120 700 600 100 500 80 Values 400 Values 60 300 40 200 20 100 0 0 8 9 10 11 0 1 2 3 4 5 6 7 8 9 1011121314151617181920212223 Times Weekdays Weekdays Source: (Chabau-Gibson 2018) Source: (Chabau-Gibson 2018) 15
TWITTER TEXT SENTIMENT DATA Twitter Sentiment Data Table 2000 Total Count 1000 0 Trust Joy Negative Positive Anger Anticipation Disgust Fear Sadness Surprise Sentiments 15
GOOGLE TRENDS DATA RESULTS Google Trends Data Pull: Search Term “Koala” ❖ Duration of 1 st Aug 2018- 27 th Nov 2018 ❖ Score over 100 showing relevance ❖ Google Trends Data Storm 16
TWITTER DATA VS GOOGLE TRENDS Twitter Data vs Google Trends Data Table 1 st Aug 2018 – 27 th Nov 2018 250 200 150 Values 100 50 0 Dates Google Trends Data Twitter Data 17 Source: (Chabau-Gibson 2018)
SUMMARY 18
THE DISCUSSION ❖ Google Trends and Twitter data can provide new insights to public engagement globally ❖ Social media interfaces – harness as complementary data sources ❖ Koala advisory council – sparked in both data sets ❖ Positivity towards conservation methods ❖ Sentiment analysis - Twitter data sets 19
WHATS NEXT? ❖ Completion of honours thesis – March, 2020 ❖ Meeting with local authority - City of Gold Coast Council ❖ Formulation of Publication ❖ Continuation of research – PHD 20
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