Post on 13-May-2015
Using Social Media To Inform Policy Making: To whom are we listening?
Miriam Fernandez Elisabeth Cano Harith Alani
Beccy Alen
Timo Wandhoefer
Outline
• Introduc;on • Related Work • Data collec;on • Data Analysis • Conclusions
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Introduc@on
• Social media – A revolu;onary opportunity for governments to learn about the ci;zens and to engage with them more effec;vely but,
– When using social media to inform Policy Making… • To whom are we listening?
– What are the characteris+cs of those ci+zens discussing policy topics in social media?
– What are the characteris+cs of their discussions?
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Related Work (I)
• Three main lines of work – Sta;s;cs about the ci;zens’ par;cipa;on on ePlaMorms
• Not social media par;cipa;on – Sta;s;cs about users par;cipa;ng in social media
• Not narrowed to ePar;cipa;on / poli;cal discussions – Studies of poli;cal discussions in social media
• In the context of poli;cal events (elec;ons, revolu;ons, etc.), not focused on relevant topics for policy making
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Par;cipa;on in policy making
Par;cipa;on in social media
Related Work (II)
• Ci;zen’s par;cipa;on in ePlaMorms – There is a need of using social media to improve public services, reduce costs and increase transparency
– Par;cipa;on via specific online government services is generally low • Within the 27 EU countries, only 32% of individuals aged 16 to 74 have used the Internet for interac;ng with public authori;es
• Social media par;cipa;on – There is 6% more of women than men in Twi[er – 75% of users fall between 15 to 25 years of age – The average Twi[er user follows 102 users, is followed by 50 users and post 307 ;mes during her Twi[er life
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Data Collec@on • Data
– Policy topics: 76 policy topics collected from 16 PMs • German Bundestag, the State Parliament North Rhine-‐Westphalia, the state Chancellery of the Saarland and the ci;es Cologne and Kempten
– Generic topics (such as women) were filtered to avoid collec;ng noisy data -‐> 42 remaining topics • Betreuungsgeld (Care Benefit ) • Bildungspoli;k (Educa;on Policy) • Bürgerrechte (Civil Rights) • Datenschutz (Privacy Policy)
– Topics were monitored in Twi[er for a week
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Init Date Final Date Num Posts Num Users
04/01/2014 12/01/2014 17,790 8,296
Data Analysis (I) • Top contributors
– Less than 6% of the users are responsible for 36% of the content – 73.4% of top-‐contributors are NOT ci;zens but news agencies and other organisa;ons
• The average contributor to policy discussions – Is more ac;ve, popular and engaged than the average Twi[er User • (Average user discussing policy in our dataset) follows 630, is followed by 1365 and has posted 9578 ;mes during her life on Twi[er
• (Beevolve, 2012) Avg Twi[er User: follows 102, is followed by 50, posts 307
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Names of the top contributors
Data Analysis (II) • Geographic Distribu@on of Users
– Higher concentra;on of users occurs in cons;tuencies of high popula;on density
– Users engaged in social media conversa;ons around policy topics tend to be geographically concentrated in the same regions than users engaged in ePar;cipa;on plaMorms
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(a) Distribution of eParticipation projects (b) Distribution of Twitter users
Figure 1: (a) Distribution of eParticipation projects in Germany (http://www.politik.de/politik-de/projekte_entdecken/beteiligungskarte) (b) Distribution of Twiter users: yellow are locations with less than 10 users, pink are locations with 10 to 50 users, red are locations with more than 50 users
Data Analysis (III)
• Topic Distribu;on – Few topics are extensively discussed during the analysed period
• Privacy, Network Policy, Minimum Wage, Copyright, etc. – The majority of topics are underrepresented
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Data Analysis (IV)
• Sen;ment Distribu;on – Top Nega;ve topics
• Gene;c Engineering • Immigra;on • Dona;ons to poli;cal par;es
– Top Controversial topics (High percentage of posi;ve and nega;ve posts) • Privacy • Fracking
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Use Sen;Wordnet German lexicon to compute sen;ment
Limita@ons of the data/analysis
• Data available at: – h[p://kmi.open.ac.uk/people/miriam/ECSM2014/dataset.zip
• This is a confined study – Data collected only for one social media plaMorm (Twi[er) – Data collected only for the German language – Data collected only for a limited period of ;me – Tweets with geo-‐coordinates are very scarce
• Users geolocated by using their profile informa;on + Google services – Concrete sta;s;cs about the geographical distribu;on of users engaged in ePar;cipa;on plaMorms in Germany not available • Assump;on: regions with high number of ePar;cipa;on ini;a;ves are also those ones where more users are engaged in ePar;cipa;on
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Conclusions
• Understanding who are the users discussing policy in social media and how policy topics are debated could help PMs assessing how their views and opinions should be weighted and considered to inform policy making
• Main highlights of this study – A high volume of conversa;ons around policy topics does not come from ci;zens, but from news agencies and other organisa;ons
– Users discussing policy topics in Twi[er are more ac;ve, popular and engaged than the average twi[er user
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