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What do Twitter conversations tell us about petitioning?

Talk by Prof. Cristina Leston Bandeira and Dr. Viktoria Spaiser at the Parliament, Data and Democracy meetup

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What do Twitter conversations tell us about petitioning?

  1. 1. Prof. Cristina Leston Bandeira, School of Politics and International Studies Dr. Viktoria Spaiser, School of Politics and International Studies With Molly Asher, Data Science Intern, Leeds Institute for Data Analytics What do Twitter conversations tell us about petitioning?
  2. 2. • 2015 • 10,000 signatures (government response), 100,000 signatures (considered for a debate) • Wide ranging public engagement initiatives – including Twitter • Aims: o open up, o give a direct channel people–parliament, o enhance relationship Background
  3. 3. Key question: Do petitions enhance engagement with Parliament? • New system’s processes: clear and transparent. • But are they perceived as worthwhile by the public? • Debate: the highlight of petitioning. How is it perceived by the interested public? • Petitions debated March-Nov 2016 • Ban grouse shooting petition • Comparison of reactions to debate and oral evidence session • #GrouseShooting Background
  4. 4. 1. What can Twitter conversations tell us about the extent to which individuals engage in the petition process beyond the signing stage? 2. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? 3. Who gets involved in conversations about e-petitions and how do they interact? • Collection of all Twitter data tagged with a specific hashtag (defined by Petition Committee) • Twitter Streaming API Twitter Data
  5. 5. • Data processed, analysed and visualised with Python, R and Gephi • Extracting key information, e.g. how mange Twitter users participated in a petition debate on Twitter • Topic identification: N-gram based semantic network • Social Network Analysis based on retweet patterns • Automatic Sentiment analysis with AFINN-111 online lexicon • Twitter User Classification with Naïve Bayes Classifier • Quadratic Assignment Procedure (QAP) analysis to test homophily Data Analysis nodes = words/Twitter users weighted edges = frequency of co-occurrence of two words/ retweet frequency + community detection algorithm (Lovian method)
  6. 6. What can Twitter conversations tell us about the extent to which individuals engage in the petition process beyond the signing stage? Title of issue Hashtag Number of signatures Number of tweets Number of users involved Invoke Article 50 of The Lisbon Treaty immediately. #exitingtheeudebate 127,111 32 23 Debate in the House the Local Government Pension Scheme Investment Regulations #lgps 105,772 25 23 Ban driven grouse shooting #grouseshooting 123,077 7,364 2,704 Urge the South Korean Government to end the brutal dog meat trade #DogMeatTrade 102,131 2,997 1,113 Stop retrospective changes to the student loans agreement #StudentLoanDebate 133,969 86 81 Include expressive arts subjects in the Ebacc #EbaccDebate 102,499 3,283 1,451 Stop spending a fixed 0.7 per cent slice of our national wealth on Foreign Aid #UKAidDebate 235,979 7,474 3,092 Stop Cameron spending British taxpayer's money on Pro-EU Referendum leaflets #EUReferendumLeafl et 221,866 48 41 Give the Meningitis B vaccine to ALL children, not just newborn babies. #menb 823,348 141 87 Keep the NHS Bursary #NHSBursary 162,568 447 292 The DDRB's proposals to change Junior Doctor's contracts CANNOT go ahead. #JuniorDoctors 110,065 224 176 Make an allowance for up to 2 weeks term time leave from school for holiday. #termtimeholiday 127,199 4 4 Fund more research into brain tumours, the biggest cancer killer of under-40s (April) #braintumourresearc 120,129 630 282 EU Referendum Rules triggering a 2nd EU Referendum #EURefDebate 4,149,757 6 4 Make it illegal for a company to require women to wear high heels at work #heelsatwork 152,420 272 75 Restrict the use of fireworks to reduce stress and fear in animals and pets #FireworkDebate 104,038 92 50 Results
  7. 7. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? • RT @Third_Position: Anecdotal gibberish. #GrouseShooting has been around for centuries & hunting is ancient. They help conserve these animals • RT @WildlifePhelps: "We are losing a species and this is a crisis" Finally an MP states the real reason for the petition! Excellent. #grousesooting • Red_eyed_video "If that was a debate it's no surprise the country's in a mess“ #grouseshooting Results
  8. 8. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? Topic cluster: Positives of hunting • Masculinity • Primal • Father • Son • Bond • Thirdposition • Shot • Food Results
  9. 9. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? Topic cluster: Consequences of hunting • Heather • Flooding • Henharrier • Ecology • Calderdale • Environment • Review • Study Results
  10. 10. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? Topic cluster: Criticism of Debate • Frustrating • Polarised • Bias • Praising • Favouring • Stevedouble
  11. 11. Oral Evidence session • Allows petition creator and others to present evidence • Difference in reaction to between the forms of parliamentary sessions How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? Results
  12. 12. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? Results
  13. 13. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? Results
  14. 14. Who gets involved in conversations about e-petitions and how do they interact? • The size of the nodes show their centrality • Most influential users are already politicians/campaigners • Nodes of same colour interact with each other more than with others of different colours Results Debate Oral Evidence Session
  15. 15. Who gets involved in conversations about e-petitions and how do they interact? Naïve Bayes Classifier results + Quadratic Assignment Procedure (QAP) analysis suggests significant homophily in the social network  retweeting those you already agree with  Polarisation and closed communities Results
  16. 16. • Conversations on twitter can help us to understand more about the e-petitioning system: 1. Often people sign a petition and then forget about it. The number of people who engage on Twitter varies massively. Protest vs Substantive petitions 2. People are using Twitter as a means of publicising debates and pressuring their MPs to attend, but also as a means of expressing views on parliamentary process. Difference in reactions between debate and oral evidence suggest reflection on nature of debates. 3. Twitter conversations show homophily and polarisation: online discussions reinforcing people’s views rather than contributing to wider consideration of points of view. Though, less so when @HoCPetitions live tweets. Suggests it can play useful role to consider range of arguments on petition. Preliminary conclusions
  17. 17. Thank you @estrangeirada @Viktoria_Sp
  18. 18. What can Twitter conversations tell us about the extent to which individuals engage in the petition process beyond the signing stage? • E-petition just the first stage • Is signing a petition too easy? • Is it ‘slacktivism’? • Twitter is one way to maintain engagement, but how many people use it…..?
  19. 19. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? Word 1 Word 2 Weight debate grouseshooting 1931 ban grouseshooting 853 grouse grouseshooting 739 driven grouseshooting 722 grouseshooting mps 567 ban debate 487 debate mps 483 grouse shooting 475 grouseshooting moors 403 ban driven 378 debate grouseshooting “You may know a word by the company it keeps” – John Firth
  20. 20. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? Ignoring of Lucas intervention • Depressingly • Peat • Dismissed • Importance • Highlight • Climatechange • Uplands • CarolineLucas
  21. 21. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? Tweets: Debate • Chrisgpackham • natalieben • leagueacs • markavery • campaigners • Directed • Attack • Vitriol
  22. 22. How are individuals engaging through Twitter with e-petitions and to what extent do their discussions inform us about their reactions to the e-petition process? word n Sentiment score Overall sentiment Sentiment Contribution admit 67 -1 negative -67 appalled 94 -2 negative -188 attack 91 -1 negative -91 ban 1,357 -2 negative -2714 benefit 47 2 postive 94 bias 366 -1 negative -366 care 72 2 positive 144 crap 24 -3 negative -72 cruel 79 -3 negative -237 dead 64 -3 negative -192 death 137 -2 negative -274 depressed 113 -2 negative -22
  23. 23. Who gets involved in conversations about e-petitions and how do they interact? User 1 User 2 Weight 0GreenCat Greens4Animals 28 saysPRnow Greens4Animals 27 rdepledge Gameandwildlife 26 Greens4Animals Greens4Animals 21 Londononlytime Third_Position 21 kevinjholmes Gameandwildlife 20 kevinjholmes ShootingTimes 20 pip_tp ShootingTimes 10 BASCsimon Gameandwildlife 9 countrygent9 Gameandwildlife 9 0GreenCat Greens4Animals
  24. 24. Who gets involved in conversations about e-petitions and how do they interact? Pro Anti Pro Anti ProAnti Anti Anti

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