Pierangelo MASSA & Michele CAMPAGNA University of Cagliari, DICAAR COST ACTION TD1202 ESR EVENT 23 – 24 April 2015 IMREDD - Nice, FRANCE Mapping and the

Pierangelo MASSA & Michele CAMPAGNAUniversity of Cagliari, DICAAR

COST ACTION TD1202ESR EVENT

23 – 24 April 2015 IMREDD - Nice, FRANCE

Mapping and the citizen sensor

COST Action TD1202Mapping and the citizen sensor

Social Media Geographic Information (SMGI): analytical opportunities for spatial planning

Pierangelo Massa and Michele Campagna

University Nice Sophia Antipolis@IMREDD April 23-24 2015

Università di Cagliari





Contents Introduction

Current practices with SMGI

Analytical opportunities for spatial planning

Our approach for SMGI analytics

Example case studies

Results and further research





IntroductionUnprecedented availability of digital Geographic Information:

SUPPORT

ANALYSIS, DESIGN

DECISION-MAKING

Authoritative Geographic Information (A-GI)

Volunteered Geographic Information (VGI)

Social Media Geographic Information (SMGI)





Current practices with SMGI

Disaster management response efforts – situation awareness – real-time analysis

Political events statistical reports – trends analysis

Media events events detection

Social studies sentimental analysis – semantic analysis – behavioral analysis

Urban planning land use investigation – urban movement – geodemographics

SMGI are increasingly used in diverse fields thanks to embedded Geo-information:





Analytical opportunities for spatial planning Opportunities:

Citizens as volunteered (or un-volunteered) sensors for Geographic Information

Movement, interests, opinions, needs and experiential knowledge of community

Novel analytical frameworks for coupling Space, Time, User and Contents

Issues:Data Harvesting: new tools to collect social information

Data Management: Big Data analytics to manage, integrate and analyze information

Information Reliability: quality and credibility





Our approach for SMGI analytics Spatext tool

Add-in for ESRI ArcGIS

Developed in Python 2.7

Connected to 5 social media

Harvest and manage data from social media

Geocode and georeference data

Temporal and Textual analysis

Spatial-User clustering





Disaster event: the Cyclone Cleopatra Spatial distribution of 399 tweets for keyword “Sardinia floods” Cyclone occurred in Sardinia 18 November 2013





Disaster event: the Cyclone Cleopatra Temporal analysis: trend and peaks Textual analysis: tag cloud Italy & World





Spatial distribution of 180 video at Regional Scale

Perception: ‘Landscape’ in Sardinia





Semantic analysis: semantic classification of words in title and caption of video

Tag Cloud analysis:tag-cloud analysis of most used words in title and caption of video

Perception: ‘Landscape’ in Sardinia





Spatial distribution of 395 video in neighborhoods and park at the local scalePerception: Cagliari neighbourhoods





The results define a clear image of the overall perception of users:

• CASTELLO: historical building, places, ways and traditional events• MARINA: celebrations and specific buildings (church and harbor)• IS MIRRIONIS: football related activities and urban park• MOLENTARGIUS PARK: toponyms, flora and fauna

Textual analysis: tag-cloud analysis of words in title and descriptionPerception: Cagliari neighbourhoods





Land use detection: Iglesias municipality

Photo Dataset : metadata

Place

User / UserID / UserPIC

Media URL

Data Publication

n° Likes / Comments

Caption / Tags

Spatial distribution of 13951 photos posted by 1243 users for 1 year Analysis: 89% of photos within established settlements





Land use detection: temporal analysis Temporal analysis: investigation of patterns

Seasons Months Days

Workdays Weekends





Land use detection: spatial clustering

Results:

290 clusters

public places

368 clusters

personal places

Spatial analysis: cluster detection using Density-Based scan (Ester et Al, 1996) Detection of popular places for local community and personal places of users





Land use detection: identifying public places

Results: A

BC D

E

A = Cathedral

B = Historic Plaza

C = Main avenue

D = Main Plaza

E = Public Garden

Why these clusters?





Public places: (A) Cathedral

A A

SMGI related to the Cathedral of Santa Chiara





Public places: (B) Historic Plaza

B B

SMGI related to the Plaza La Marmora





Public places: (C) Main Avenue

C C

SMGI related to the Main Avenue Via Matteoti





Public places: (D) Main Plaza

D D

SMGI related to the Piazza Sella





Public places: (E) Public Garden

EE

SMGI related to the Giardini Pubblici





Land use detection: residential areas

Used parameters cluster centroid Yes photo barycenter Yes number of photo => 5 photo/area => 4 Intersections <= 2 photo time dist. => 30

Results: 50 residential clusters

Spatial analysis: how to detect ‘residential areas’ from clusters?





Land use detection: missing buildings Spatial analysis: how to identify missing buildings in A-GI?

Used parameters cluster centroid No photo barycenter No number of photo => 5 photo/area => 4 Intersections <= 2 photo time dist. => 30

Results: 40 clusters 9 not mapped buildings

A = mapped buildingB = not mapped buildingC = mapped buildingD = not mapped buildingE = mapped buildingF = mapped building





Results and further development

Integration of further Social Media platforms in Spatext: Flickr, Panoramio, Vkontakte, Booking.com

Implementation of sentiment analysis Formalization of SMGI analytics for practices

Spatext tool for SMGI analytics Integration with standard GIS tools Spatial-Temporal Textual analysis Topics trend, Perceptions and Topography from SMGI Pluralist information with professional knowledge Innovative methods for supporting urban and regional planning





Thank you for your attention!

Pierangelo MASSA

University of Cagliari

[email protected]

Michele CAMPAGNA

University of Cagliari

[email protected]

Documents

Pierangelo MASSA & Michele CAMPAGNA University of Cagliari, DICAAR COST ACTION TD1202 ESR EVENT 23 – 24 April 2015 IMREDD - Nice, FRANCE Mapping and the