Exploring the advances in using social media data for conservation science

Transcription

1 Exploring the advances in using social media data for conservation science Workshop at the 5th European Congress of Conservation Biology (ECCB), Jyväskylä, Finland Tuesday, June 12, am - 1pm Room K309 Gustaf

2 Schedule 11 am 1pm Introductions Presentation: recent advances in social media analysis for conservation science Group brainstorming: Which research topics could be addressed using social media data? Report your ideas in the Flinga whiteboard Short break General discussion: What can be done in practice? Together, we will organize the topics in the whiteboard according to how doable they are Wrap up

3 Recent advances in Social Media Data Analysis for Conservation Science Enrico Di Minin, Tuuli Toivonen, Vuokko Heikinheimo, Anna Hausmann & Christoph Fink, Tuui Toivonen Digital Geography Lab, University of Helsinki

4

5 Social media data in conservation 1. THREATS 2. OPPORTUNITIES

6 Elements of a social media post USER INFO GEOTAG TIMESTAMP TEXT CONTENT IMAGE CONTENT LIKES & COMMENTS

7

8 Di Minin, Tenkanen & Toivonen (2015) Frontiers in Environmental Science

9 Proportion of Visitors/ users r= Month

10 PALLAS-YLLÄS NATIONAL PARK

11 PALLAS-YLLÄS NATIONAL PARK Posts from a Finnish Instagram-user. 107 posts in total.

12 PALLAS-YLLÄS NATIONAL PARK Rogers Pass Summit, Canada Schladming-Dachstein, Austria Pallas-Yllästunturi National Park, Finland Posts from a Finnish Instagram-user. 107 posts in total.

13 Source:

14 Source:

15 Social Media Data Analysis Pipeline Spatial analysis Temporal analysis Network analysis WHERE, WHEN, WHAT, WHY, WHO DATA MINING CLEANING FUSION ANALYSIS RESULTS Place-based search Topic-based search User-based search Bot detection Outlier detection Combining complementary data sources Content analysis Manual Automated Crowdsourced Validation

16 Comparison of Instagram and Flickr data Instagram 2015: Whole city: posts by users Green areas: posts by users Flickr 2015: Whole city: posts by 900 users Green areas: 6700 posts by 400 users

17 Comparison of Instagram and Flickr data Instagram Flickr Instagram 2015: Whole city: posts by users Green areas: posts by users Flickr 2015: Whole city: posts by 900 users Green areas: 6700 posts by 400 users

18 Comparison of Instagram and Flickr data Instagram Flickr GREEN AREA 40% 7% LANDSCAPE 30% GREEN AREA 56% 4% LANDSCAPE 18 % ACTIVITY 23% ACTIVITY 22% Content types of manually classified Instagram photos (n=9200) and Flickr photos (n=1700) from Green areas in Helsinki.

19 Spatial Precision and Accuracy 10 km Analysis scale! Digital footprints from a game drive in Kruger National Park, South Africa

20 Hausmann, A., Toivonen, T., Slotow, R., Tenkanen, H., Moilanen, A., Heikinheimo, V., & Di Minin, E. (2017). Social Media Data Can Be Used to Understand Tourists Preferences for Nature-Based Experiences in Protected Areas. Conservation Letters.

21 Manual content classification

22 Manual content classification

23 Survey vs social media data Two-sample Kolmogorov-Smirnov test Instagram D = p = Flickr D = p = 0.660

24 Survey vs social media data

25 Factors affecting social media use across sub-saharan Africa s protected areas Anna Hausmann, A., Toivonen, T., Heikinheimo, V., Tenkanen, H., Slotow, R. & Minin, E.D. (2017). Social media reveal that charismatic species are not the main attractor of ecotourists to sub-saharan protected areas. Sci. Rep., 7. doi: /s

26 Factors affecting social media use across sub-saharan africa s protected areas Higher Human Development Index Lower travel cost Lower vegetation density Higher population density around the area Lower richness of biodiversity No Effect! richness of charismatic species

27

28

29 Increasing evidence of illegal trade in wildlife moving onto social media Chung et al., 2017, Harrison et al. 2016, Hastie and McCrea-Steele, 2014 (IFAW report), Analysis of social media data, carried out manually, is laborious Tools for automatically analysing text and image content exist and are successfully applied in other fields

30 Di Minin et al., under review

31 Di Minin et al., Nature Ecology & Evolution, 2018

32 #rhino

33

34 THANK YOU! - SOCIAL MEDIA DATA FOR CONSERVATION SCIENCE INVESTIGATING ILLEGAL WILDLIFE TRADE DIGITAL GEOGRAPHY LAB

35 Literature Di Minin, E., Fink, C., Tenkanen, H., & Hiippala, T. (2018). Machine learning for tracking illegal wildlife trade on social media. Nature Ecology & Evolution, 2(3), DOI: /s x Tenkanen, H., Di Minin, E., Heikinheimo, V., Hausmann, A., Herbst, M., Kajala, L., & Toivonen, T. (2017). Instagram, Flickr, or Twitter: Assessing the usability of social media data for visitor monitoring in protected areas. Scientific Reports, 7, [17615]. DOI: /s Hausmann, A., Toivonen, T., Heikinheimo, V., Tenkanen, H., Slotow, R., & Di Minin, E. (2017). Social media reveal that charismatic species are not the main attractor of ecotourists to sub-saharan protected areas. Scientific Reports, 7, [763]. DOI: /s Heikinheimo, V., Di Minin, E., Tenkanen, H., Hausmann, A., Erkkonen, J., & Toivonen, T. (2017). User-Generated Geographic Information for Visitor Monitoring in a National Park: A Comparison of Social Media Data and Visitor Survey. ISPRS International Journal of Geo-Information, 6(3), [85]. DOI: /ijgi Hausmann, A., Toivonen, T. K., Slotow, R., Tenkanen, H. T. O., Moilanen, A. J., Heikinheimo, V. V., & Di Minin, E. (2017). Social Media Data Can Be Used to Understand Tourists Preferences for Nature-Based Experiences in Protected Areas. Conservation Letters, 11(1). DOI: /conl Di Minin, E., Tenkanen, H. T. O., & Toivonen, T. K. (2015). Prospects and challenges for social media data in conservation science. Frontiers in ecology and evolution, 3, [63]. DOI: /fenvs

36 Group brainstorming: Which research topics could be addressed using social media data? (20 min)

37 Flinga whiteboard 1. Go to flinga.fi on your laptop or mobile device 2. Join a session with the access code: F75HANH Or use the Direct link:

38 Flinga.fi, Session: F75HANH Pick a color for your group Write an idea here and press Send also feel free to use pen and paper

39 General discussion: What can be done in practice? Together, we will organize the topics in the whiteboard according to how doable they are.

40 Hungry for more? Time Room Presentation Wed at 12:25 K305 Alvar Anna Hausmann: Assessing global tourism visitation of Important Bird Areas by using social media data Thu at 11:15 A2 Wivi Enrico Di Minin: Social media data for conservation science and practice Thu at 11:30 K309 Gustaf Christoph Fink: Uncovering Illegal Wildlife Trade on Social Media

41 THANK YOU! - SOCIAL MEDIA DATA FOR CONSERVATION SCIENCE INVESTIGATING ILLEGAL WILDLIFE TRADE DIGITAL GEOGRAPHY LAB