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Bringing Citizens’ Opinions to Members of Parliament

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Bringing Citizens’ Opinions to Members of Parliament

  1. 1. Bringing Citizens’ Opinions to Members of Parliament The Newspaper Story Ruxandra Geana Steve Taylor Timo Wandhoefer CeDEM2012, Donau Universität Krems
  2. 2. Contents• Background & Context• Problem Statement• Solution Strategy• Results• Conclusions & Further Work
  3. 3. Background
  4. 4. Context: WeGov Project• Allow policy makers to interact directly with citizens using Social Network Sites – Use the tools the citizens already use• Find and understand people’s opinions• Become part of the discussion• Open dialog• Respect privacy• Encourage trust
  5. 5. WeGov Toolbox SearchAnalysis Analysis
  6. 6. Scenario
  7. 7. Scenario• Policy makers want to test policy statements with citizens• Direct contact on SNS can be inefficient• Often policy statements are issued as press releases – Newspaper articles written about them – These are discussed across social media – We need to find where the comments are made on policy statements• We can then use other tools in the toolbox to collect postings and provide further analysis
  8. 8. Scenario
  9. 9. Research Questions& Strategy to Answer Them
  10. 10. Research Questions & Answers1. How can we find out where a 1. Google for the headline and URL news article is being discussed? of the article2. How can we track the locations for 2. Schedule repeated automatic 1) over time? searches and store ranked results3. How can we track a news story 3. Group searches into stories containing many news articles?4. How can we find news articles 4. Search specific newspaper sites related to a press release or an for press release MP’s statement?5. Which are the important places a 5. Group searches into subject areas policy maker needs to monitor for & record top tens a particular subject area?
  11. 11. Search Strategy• Google searches for news article headline & URL return sites that reference our news article• Google is by far the most popular search engine in the Western world – therefore it is very likely to be used by many people who may want to comment on a news article• Google’s ranking is important – it scores pages by relevance and the number of citations – therefore popular pages that reference our news article will be ranked highly
  12. 12. Basic Components Search Google for the articles’ Find news URL & headline articles Configure Scheduler to repeat search at defined intervals News Article Search URL + Headline Scheduler User Data Selection Internet Google Custom Search Database Date: ??? Display & Data Results: Headline Search 1 www L Analysis 2 3 www G www M Story, Press Release, Minister’s Statement 99 4 5 www J www A ... www Store rankedAggregated Results: 1 2 3 Day 1 www A www J www Q Aggregated Results: 1 2 3 Day 2 www J www A www Q Aggregated Results: 1 2 3 Day 3 www K www J www Q Aggregated Results: 1 2 Day n www AA www J Analyse 100 URL Search 1 www www J search results 3 www AP 2 www K in database 4 www B 4 www M 4 www P 4 www AE 5 www W 5 www W 5 www X 5 www AW 3 www F 6 www X 6 www K 6 www A ... 6 www AC 4 www D results 7 www K 7 www X 7 www S 7 www K 8 9 www L www M 8 9 www L www B 8 9 www W www M 8 www L 5 www E 9 www AM ... 10 www 10 www 10 www 10 www ... ... ... ... 99 www 99 www 99 www 99 www 99 www 100 www 100 www 100 www 100 www 100 www time
  13. 13. Illustration of Searches Over Time News Article Date: 5 June 2011 Date: 7 June 2011 Date: 9 June 2011 Date: 11 June 2011 Date: ??? Results: Results: Results: Results: Results: Headline Search Headline Search Headline Search Headline Search Headline Search 1 www A 1 www B 1 www G 1 www G 1 www L 2 www B 2 www A 2 www H 2 www J 2 www G 3 www C 3 www C 3 www B 3 www B 3 www M 4 www 4 www G 4 www A 4 www A 4 www J 5 www 5 www 5 www 5 www 5 www A ... ... ... ... ... 99 www 99 www 99 www 99 www 99 www 100 www 100 www 100 www 100 www 100 www URL Search URL Search URL Search URL Search ... URL Search 1 www D 1 www D 1 www F 1 www F 1 www J 2 www E 2 www E 2 www D 2 www J 2 www K 3 www F 3 www F 3 www E 3 www K 3 www F 4 www 4 www 4 www 4 www D 4 www D 5 www 5 www 5 www E 5 www E ... ... ... 99 www 99 www 99 www 100 www 100 www 100 www time• Sites referencing the news article change over time• “Pop Charts” of Rankings – sites rise & fall, new entrants
  14. 14. Analysis: Selection & Aggregation• Data can be analysed in different ways• Select a subset of data – e.g news story or subject area, each with many articles • how do the locations change over time? • what is the top location over all times?• Other examples: – select all news stories in a subject area – select all news stories in one week – select news stories from one publisher
  15. 15. News Stories, Articles & OLAP• One news story – Multiple news articles (z axis) – Multiple searches over time per article (x axis)• We can “collapse” x and z axes to get averages for all values of that feature
  16. 16. Averaging• Bayesian average chosen to average chart positions – Takes account of number of samples each web site has – The more instances a site has, the more sure we are that its position is accurate• Avoids spurious end-members
  17. 17. Illustration
  18. 18. Main UI News ScheduledHeadlines search results
  19. 19. Most Popular Domains Loweraverage is Over All Searches better Can blacklist sites
  20. 20. Top Domains forSelected Searches Select a News Story and a time frame
  21. 21. Popular DomainsChanging Each Week
  22. 22. Conclusions• A governmental policy maker can discover where comments are made on policy statements – Often news articles are written about policy statements and the articles are discussed over the internet• We use scheduled and repeated Google searches for news articles and collect the results in a database – We can aggregate analyse search results to produce ranked tables of sites that reference each news article• Using data mining techniques such as the OLAP cube, we can group data in many ways – We can examine aggregate scores taking into account multiple datasets, averaging out individual differences

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