News, Numbers and Public Opinion in a Data-Driven World ii News, Numbers and Public Opinion in a Data-Driven World Edited by An Nguyen Bloomsbury Academic An imprint of Bloomsbury Publishing Inc N E W YO R K • LO N D O N • OX F O R D • N E W D E L H I • SY DN EY Bloomsbury Academic An imprint of Bloomsbury Publishing Inc 1385 Broadway 50 Bedford Square New York London NY 10018 WC1B 3DP USA UK www.bloomsbury.com BLOOMSBURY and the Diana logo are trademarks of Bloomsbury Publishing Plc First published 2018 © An Nguyen and Contributors, 2018 All rights reserved No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage or retrieval system, without prior permission in writing from the publishers No responsibility for loss caused to any individual or organization acting on or refraining from action as a result of the material in this publication can be accepted by Bloomsbury or the author Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: HB: 978-1-5013-3035-3 ePDF: 978-1-5013-3037-7 eBook: 978-1-5013-3036-0 Cover design by Jason Anscomb Typeset by Deanta Global Publishing Services, Chennai, India To find out more about our authors and books visit www.bloomsbury.com Here you will find extracts, author interviews, details of forthcoming events, and the option to sign up for our newsletters Contents List of Contributors Foreword Stuart Allan Introduction: Exciting Times In the Shadow of the ‘Post-Truth’ Era: News, Numbers and Public Opinion in a Data-Driven World An Nguyen Exciting times Numbers as a staple of modern life The age of dubious numbers and ‘statistical bullshit’ The crucial but largely forfeited role of journalism This book’s intervention References x xv 1 14 Section One Data and Statistics in News Production Common Statistical Errors in the News: The Often-Unfulfilled Roles of Journalists in Statistics–Society Relationship Fabienne Crettaz von Roten Introduction Some common misuses of statistics in the media The three unfulfilled roles of journalists Concluding notes References More Light, Less Heat: Rethinking Impartiality in Light of a Review into the Reporting of Statistics in UK News Media Stephen Cushion and Justin Lewis Introduction Interpreting the quantitative supply of statistics in news reporting Everyday reporting of statistics in UK news media: An overview Case study 1: The UK Prime Minister’s claim about EU migrants claiming benefits 19 19 20 23 26 28 32 32 33 34 35 vi Contents Case study 2: Reporting changes to tax credits system 38 Rethinking impartiality: Challenging statistical claims 44 References 46 Numbers That Kill: How Dubious Statistics Shaped News Reporting of 47 the Drone War Muhammad Idrees Ahmad Introduction 47 A history of violence 48 How rituals of objectivity bias statistics in the media 49 Drones and statistical misfires in news coverage: A case study 51 Limits of contrarianism 58 References 59 Poor Numbers, Poor News: The Ideology of Poverty Statistics in the 62 Media Jairo Lugo-Ocando and Brendan Lawson Introduction 62 The circular logic 64 The definitional morass of who is poor 67 Over-reliance on ‘official sources’ 70 Towards a conclusion 73 References 74 Statistics in Science Journalism: An Exploratory Study of Four Leading 78 British and Brazilian Newspapers Renata Faria Brandão and An Nguyen Introduction 78 Journalistic deference to statistics 79 Can science journalism be an exception? 80 Our exploratory content analysis 84 Concluding notes 88 References 90 Data Journalism at its Finest: A Longitudinal Analysis of the Characteristics of Award-Nominated Data Journalism Projects Julius Reimer and Wiebke Loosen Introduction: Journalism’s response to the datafication of society What we (don’t) know about data journalism Our content analysis of DJA-nominated/awarded projects Findings Discussion: Retracing the development of DJA-nominated stories References 93 93 94 95 97 109 111 Contents vii 7 Numbers Behind the News: Audience Metrics and the Changing Nature of Gatekeeping An Nguyen and Hong Tien Vu Introduction The powerless news audience in traditional gatekeeping The penetration of web metrics into the newsroom The many risks of metrics-driven audience agenda Beyond head counting: Harnessing the power of audience metrics References 113 113 114 116 120 124 127 Section Two Data and Statistics in News Consumption The Power of Numbers, Reconsidered Scott R Maier Introduction The power of numbers Psychic numbing and compassion fatigue Combining personification with statistics: Nicholas Kristof ’s approach to psychic numbing Numerically versus non-numerically based news: An experimental study on reader responses Conclusion: The quantitative paradox References Big Data, Little Insight: Anecdotal and Quantitative Descriptions of Threatening Trends and their Effects On News Consumers Charles R. Berger Introduction Anecdotal depictions of hazards and threats Quantitative depictions of threatening trends Individual and social consequences of statistical distortions Conclusion References 133 133 134 135 136 138 140 142 144 144 146 149 157 159 161 10 Effects of Statistical Information in News Reports On Individuals’ Recall and Understanding of Events and Issues: Implications for Journalistic Practices Rhonda Gibson and Coy Callison Introduction Exemplification theory of media effects Presentation formats The role of arithmetic ability 163 163 164 166 168 viii Contents Implications for journalists and other public communicators References 11 Numbers in the News: More Ethos Than Logos? Willem Koetsenruijter Introduction How well consumers process numbers in the news? Numbers and public perception of news issues Numbers as a rhetorical device Numbers and the perceived credibility of news Conclusion References 171 173 177 177 178 180 181 182 187 188 12 Audience Uses and Evaluations of News Visualizations: When Does an Infographic say More than a Thousand Words? Yael de Haan, Sanne Kruikemeier, Sophie Lecheler, Gerard Smit and Renee van der Nat Introduction Visualizations in the news: An upcoming storytelling genre Methodology Results Concluding notes: Implications for news industries and journalism scholarship References 191 191 192 195 197 201 202 Section Three Agenda for the Future 13 Towards a Fruitful Relationship Between Statistics and the Media: One Statistician’s View Kevin McConway 209 Introduction 209 If statistics are so boring, why are the news media so full of them? 210 Statisticians and media processes 214 The strange case of mobile phones and brain tumours 216 How should the public read statistical news stories? 220 Advice for statisticians on working with journalists 222 References 224 14 Mind The Statistics Gap: Science Journalism as a Bridge Between Data and Journalism Holger Wormer 226 Introduction 226 Numbers and figures: News or just nice? 227 Contents Data and databases as ‘automatic news value generator’ The limits: Daunting data and the statistical skills of everyday journalists Media sections of hope: Science and economy The common roots of data-driven journalism and science journalism Mainstream data journalism of today: Doing some statistics or just visualization? Towards a next generation data (analysis) journalism Conclusions and perspectives Acknowledgements References ix 228 229 230 231 233 234 237 239 239 15 Teaching Statistical Reasoning (Or Not) in Journalism Education: Findings and Implications from Surveys with US J-Chairs Robert J Griffin and Sharon Dunwoody Introduction Statistical reasoning Research questions Method Results Implications for the future of statistical reasoning in journalism curricula References Appendix 242 242 243 245 245 247 253 256 258 16 Four Conceptual Lenses for Journalism Amidst Big Data: Towards an Emphasis on Epistemological Challenges Oscar Westlund and Seth C Lewis Introduction The expertise, economics and ethics of big data and journalism The epistemology of big data and journalism: Current research The epistemology of big data and journalism: Directions for future research References Index 260 260 261 267 270 272 277 274 News, Numbers and Public Opinion in a Data-Driven World Kitchin, R and McArdle, G (2016), ‘What makes big data, big data? 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Trump’s controversial election agree–disagree scale 246 American Statistical Association 245 n.6 America Online (newsroom) 122 anti-free trade movements 73 arithmetic ability, role of 168–71 affect-mediated risk-related assessments 170 assessments of 168 change in worldview information 171 conceptual and operational definitions 169 individuals with low arithmetic aptitude 170 individuals with high numeracy process 169 information about illness rates 170 International Survey of Adult Skills 168 non-numeric information 169 quantitative literacy 170 arson-caused wildfires 144 in California 145 relatively rare 145 Aryana Institute for Regional Research and Advocacy 57 attitude/belief formation 10 audience agenda 120 metric-driven, risks of 120–4 audience analytics 113 audience channel 116 audience data philosophy 124, 126 audience metrics 120 harnessing the power of 124–7 risks of 120–4 audience-tracking data 113 Ausserhofer, Julian (fellow researcher) 96 automatic news value generator data and databases 228 news values 228 Bacon, Francis (natural philosopher) 81 BBC, variation in news editorial guidelines 32 Radio 4, More or Less show 12, 210 Radio 4’s Six O’Clock News 37, 40–1 Radio 4’s Today Programme 36, 38, 41–2 Radio interview 36 radio news report 39, 41 television news on 33, 37, 40, 43 BBC Trust 8, 32, 34 quantitative part of 34 review 45 BehaveNet 135 Berners-Lee, Tim big data and journalism current research 267–70 economics 261–2, 263–5 ethics 261–2, 265–6 expertise 261–2, 262–3 future research 270–2 Bloomberg (newsroom) 122 blowback 53 blowback thesis 52 body-count statistics Bonferroni–Holm correction 104 n.5, 104 n.6 A Brief History of Time (Hawking) 229 business pages 211 278 Index California Department of Forestry and Fire Prevention’s website 144 Cameron, David (UK Prime Minister) 35 EU migrants claiming benefits 35–8 catastrophic Y2K computer failures 160 causal relationship 22, 216 n.7 non-causal relationship 216 n.7 Chartbeat (third-party software) 117, 123, 125 charticles 12, 226 Chavez, Hugo (Venezuela president) 62–3 ‘chicken and egg’ relationship circular logic 64–7 depreciation of assets 66 ‘economization’ of society 65 GDP during WW2 66 management of poverty 64 objective economic models 64 post-development school of thought 64 citizen journalism 159 CNN (Cable News Network) 126 World Today 154 Codebook 96, 109 dimensions and variables of 97 Code of Conduct of the Royal Statistical Society 20 n.1 Code of Practice for Official Statistics 35 college-level journalism programmes 245 communicating statistics communication science 159 journalism and 81 Community Appraisal & Motivation Programme (CAMP) 57 compassion fatigue as numbing effect 136 and psychic numbing 135–6 singularity effect 136 computational journalism 94, 242, 263 computer(-)assisted reporting (CAR) 94, 226, 231, 242, 255, 260, 269 Netzwerk Recherche 232 NICAR 254 Pulitzer-Prize story 232 reporting course 248 concept of credibility 184 concept of epistemology 261, 267 concept of statistical thinking 20 content analysis 84 help lay publics to understand 86–7 science statistics relevant to lay publics 85–6 contrarianism, limits of 58–60 copywriters, using numbers 182 correcting for base-rate neglect 155–7 assessment of victimization risk 156 experimental paradigm 155 numeracy levels 157 relevant base-rate information 156 sex of the individual 156 ‘correlation’ (statistical term) 20–1 pairwise correlations 199 partial correlations 249 Pearson correlation coefficient 140 point-biserial correlation 22 of structural variables 249 crowdsourcing 94, 227, 232 current research, big data and journalism 267–70 algorithms and automation 270 computer-assisted reporting (CAR) 269 epistemology 267 ‘fact’ involving interpersonal relations 268 multiple-sourcing 267 precision journalism 269 traditional news journalism 269 watchdogging in code 270 Daily Mail 177 Dallas Morning News 117 data analysis, in DJA-nominated stories 99, 101, 103 access to data 104 focus of 106 multiple coding 105 visualization 107 data-analysis journalism (DAJ) 237 see also next generation data (analysis) journalism data and databases 228, 260 Index data and statistics for future 12–14 in news consumption 10–12 in news production 8–10 data-driven journalism (DDJ) 2, 93, 149, 231 emerging form of storytelling 95 key characteristics of 94–5 precision journalism 231 scholarship on 94 and science journalism 231–3 watchdog attitude 110 data-drivenness 97, 99–104 data analysis 99, 101, 103–5 data sets 99–100, 104 data sources 99, 101–2, 104 dependency on pre-processed public data 101 datafication of society, journalism’s response to 93 data journalism 94–5 data-gathering efforts 256 data journalism (DJ) 2, 94–5, 230–1, 242 Data Journalism Awards (DJA) 9, 93 data set overview 96 of Global Editors Network 95 identifying respective pieces 95–6 intercoder reliability coefficient 96 data journalism education 27, 236 The Data Journalism Handbook (Gray et al.) 234 data journalism-oriented scholarship 93 data sets, in DJA-nominated stories 99–100, 104 data sources, in DJA-nominated stories 99, 101–2 multiple coding 104 data-spin 110 data transparency and quality 265–6 data visualizations 21, 191 comprehensive mixed-method study 192 see also infographics Datawrapper (tool) 111 definitional of poor 67–70 flaws in validity and reliability 68 humanitarian–neo-liberal ideology 69 279 network of ‘expert voices’ 67 news beat 67 as news item 67 ‘objective’ assessment 67 ‘standard of living’ model 70 symptoms of poverty 66 dehumanizing labels 55 Denmark 268 Desrosières, A (sociologist) 214 Dialogues on History (Patrizzi) 50 digital age of journalism 227 digital audience-tracking data 10 Digital Journalism (journal) 242, 261 digital news visualizations 192 appreciation or value of 192 digital technologies DJA-nominated/awarded projects 95–7 data-drivenness 97, 99–104 interactive features 97, 107–8 visualization elements 97, 104, 106–7 DJA-nominated pieces 97–8 actors producing 97–8 DJA-nominated stories data analysis 99, 101, 103–5 data sets 99–100, 104 data sources 99, 101–2, 104 dependency on pre-processed public data 101 development of 109–11 topics and formal story elements of 98–9 DJA-nominees 98–9 drones and statistical misfires 51–4 accurate and discriminative 54–6 civilian loss in Pakistan 52 counter-terrorism 56 effectiveness 56 ethical concerns 52 flawed intelligence 54 Gulf War 54 killed top al-Qaeda leaders 56 killing civilians 54 and militant backlash 54 moral hazard 52 popular 56–8 signature strikes 56 unmanned technology 53 280 drone war decoupling drone 48 dubious drone-related statistics 48 history of violence (see history of violence) as motivation 53 U-turn in 47 dual-coding theories 180 economics, of big data and journalism 13, 261–2, 263–5 actant-focused automation 265 algorithm-controlled social platforms 264 area of coverage 264 big-data personalization 264 employing technological capacities 265 media economics 264 method of coverage 264 value-creation opportunities 264 ‘economization’ of society 65 editors, downplaying commercial factors 119 Elaboration Likelihood Model 180 electronic communication systems 160 Elements of Journalism, The (Kovach and Rosenstiel) 141 environment journalism 84 epistanai 267 epistemology 13, 267 journalistic quality and 268 key elements of 270 traditional news journalism 271 epistemology, of big data and journalism 261 current research 267–70 future research 270–2 era of fake news 59 error bars 230 An Essay on the Principles of Population (Malthus) 66 ethical standards 265 ethics, of big data and journalism 13, 261–2, 265 data transparency and quality 265–6 ethical standards 265 Index inscription of values into technological systems 266 social science research ethics 266 EU migrants claiming benefits, case study 35–8 BBC’s Economics Editor’s presentation 38 ITV’s News 38 meaning/interpretation 37 unemployment benefits 36 EUROSTAT 21 exciting times 1–2 exemplification theory, of media effects 164–6 atypical exemplars 165 availability heuristics 165 exemplars 164 heuristics 165 judgement reliability 165 lab and field experiment results 165 statistical base-rate data 164 statistical vs narrative evidence 166 expertise, of big data and journalism 13, 261–2, networked interactions 263 skill sets 263 social interactions 262–3 exploiting available statistics 42–4 independent journalism 44 slippages 43 sloppy reporting 42 statistical truths 44 variations of figure 43 extrajudicial killing eye-tracking method 193, 196 data 201–2 facts, unit of knowledge 212, 212 n.4 famine 66 ‘mathematization’ of famine 66 Farron, Tim (Liberal Democrats) 41–2 FBI Uniform Crime Statistics 154 50 Facts that Should Change the World (Williams) 212 fillers 211 Financial Times 126–7 Fisher’s exact test 99 Folha de S Paulo 79 Index Forbes (newsroom) 122 frequency versus rate data 149–53 banning plastic grocery bags 149 change in base-rate of depicted threat 150 change in parameters 151 effect of plastic bag ban 150 journalists selection of data 153 percentage reduction values 150 traffic fatalities 151–2 vehicular accident fatalities 152 front-page stories 211 future research, big data and journalism 270–2 data-backed knowledge 271 form of knowledge 271–2 news into knowledge 272 ‘post-truth’ moment for media 272 production of knowledge 271 public acceptance of knowledge 271 systematic approach 271 Galilei, Galileo (natural philosopher) 81 genetic modification 83, 90 German constitution (Grundgesetz), Article 5 238 GINI coefficient 62 Global Editors Network globalization 68 Global Poverty: A Pauperising Myth (Rahnema) 65 plurality of poverty concept 65 global warming 90 Google Analytics (third-party software) 117 Google+ users 136 government of Mexico 62 cutting poverty levels 62 gross domestic product (GDP) 3, 64–66 quantifiable information 64 during WW2 66 gross national income (GNI) 71 Guardian, The 79, 126, 181, 267 Guardian’s Datablog, The 94, 104 ‘Guinness Book of World Records’ principle 227 281 ‘hard data’, evaluating organizations 180 harnessing, power of audience metrics 124–7 audience data philosophy 124, 126 editorial analytics 125 journalism as public service 124 journalists’ autonomy 125 Hawk Eye 26 hazards and threats, anecdotal depictions of 146 availability heuristic 147 freak shows in England 147 probative value 147 traffic death hazard, reporting of 148 World Trade Center terrorist attack 148 he-said-she-said-journalism 13, 226, 229–30 Het Financieele Dagblad (Dutch financial newspaper) 195 heuristic systematic model 180 history of violence and al-Qaeda 49 drone technology 49 War on Terror 48 Huffington Post 126 downsizing news team 122 humanitarian–neo-liberal ideology 69 hyper-numeric world 3, 49 Iliffe, John (African linguist) 65 impartiality 32, 212 crude form of 41 of reporting across media platforms 34 rethinking 44–5 improvement to page design 211 independent statistics 39–41 scrutiny of claim of mitigation 40 statistical data 40 Indyk, Martin (US ambassador to Tel Aviv) 47 infographics 1, 11, 177, 181, 187, 191, 211, 270 and data visualization 236 usefulness of 12, 33 information visualizations 193, 260 see also infographics 282 Index inscription of values into technological systems 266 interactive features gamified interaction 107 interactive function 108 Kruskal–Wallis test 107 n.7 personalization tools 107 interactive journalism 261 International Agency for Research on Cancer (IARC) 218 International Commission for NonIonizing Radiation Protection Standing Committee on Epidemiology 219 The International Consortium of Investigative Journalists (ICIJ, investigative journalism organization) 97, 109 International Humanitarian Law (IHL) 55 International Mobile Subscriber Identity (IMSI) numbers 56 internet 23, 135, 159, 232 need for databases 227 surveys 23 INTERPHONE Study Group 220 intrinsic truth-value xvii investigative journalism 94 Investigative Reporters and Editors (IRE) 254 ‘J-chairs’ attitudes 247–48 perceiving benefits and constraints of statistical reasoning 250–3 percentages and mean of items 258–9 supporting teaching of statistical reasoning 250 Joseph Rowntree Foundation (JRF) 69 ‘standard of living’ model by 70 Journalism (journal) 245 Journalism Career and Scholarship Guide (Jones) 245 journalism education 27, 267 data analysis 247 questionnaires 246–7 reality in 20 sampling 245–6 journalism, forfeited role of 5–7 data journalism journalism programs statistical competence word cloud journalism scholarship gatekeeping metaphor to 114 news industries and 201 journalism, teaching improving journalism education 237 interdisciplinary teaching 238 journalists’ autonomy 125 knowledge-tested reporting 237 ‘natural’ problem zone for 229 as new knowledge profession 237 precision journalism 231 professionalizing data literacy 237 as public service 124 –statistics relationship 80 triple strategy for action 237–38 journalistic deference to statistics 79–80 science as unquestionable knowledge 82 ‘strategic ritual’ of objectivity 80 journalistic epistemology 268 journalistic thinking 236 journalists agenda 223 deadlines 223 ‘interpretative’ function 67 numeric information 163 numeric literacy 164 objective terms 68 pressure to be personal 223 representative exemplars 163 and scientists 215 stereotypical views 222 journalists, reporting poverty statistics 70 to conduct statistics 71 ‘economizing’ poverty 73 overreliance on the sources 72 quantification of reality 74 to underpin ‘truth’ 70 journalists, science–society relationship 23, 80 challenges 23 critical questioning skills 28 Index embedded statistical reasoning 28 fact-checking services 24 improving statistical literacy 26 inclusion of statistical elements 25 journalism education 27 technical roles 23–4 translating information into news 24–5 trustworthiness of sources 24 journalists, statistical information implications 171–3 avoiding reading online content 173 cognizance 173 discomfort with computational tasks 171 effects of exemplar aggregation 172 practical strategies 172 presenting numeric information 171 processing health-related numeric information 173 knowledge acquisition 10 knowledge-tested reporting 237 Kristof ’s column 137–38 Kruskal–Wallis test 101 n.3 Lantern, in-house tracking software at Financial Times 117 Liberty and the News (Lippmann) xvi, Likert-type scale 246 Lippmann, Walter xvi London and Westminster Review 213 Los Angeles Times, The 269 mainstream data journalism 233–4 Mankind in the Making (Wells) Mass Communication Directory 245 Massive Open Online Course (MOOC) 209, 221 data journalism 221 introductory course for statisticians 209 A Mathematician Reads the Newspaper (Paulos) 134 Matzat, Lorenz (data journalist) 96 McCloud (comic theorist) 194 mediatization of statistics 63 media training 215 283 memory of news 179 number is the news itself 179 metadata 99 metrics-driven audience agenda 120–4 click-thinking culture 122 fundamental transformation 121 ‘news you can use’ news 121 socio-psychological dynamics of news audiences 121 ubiquitous metrics 122 Milwaukee Journal Sentinel 255 mixed-method approach 201 mobile phones and brain tumours 216–20 high news value 217 news interpretation 218 online publication 220 potentially hazardous agents, IARC classification 218 XKCD 219 modern life, numbers in age of ‘big data’ GDP 3 hyper-numeric world poverty threshold Monkey Cage blog 52 research 58 More or Less (BBC Radio series) 12, 210 Napoleonic France 62 National Adult Literacy Survey (NALS) 157 National Institute for Computer-Assisted Reporting (NICAR) 232, 254 National Public Radio 126 negative news factors 229 ‘net-native’ actors 23 New America Foundation (NAF) 55 news integration of ‘big data’ 191 number errors in 134 -numbers relationship numerically versus non-numerically based 138–40 quantitative paradox 140–1 News & Numbers (Cohen) 134 news beat 67, 81–2, 231 science journalism 78 284 Index news consumers 178 appreciating data visualizations 199–200 attractive visualizations 200 dwell time between modalities 198 impact of numbers 178 mixed-method study 11 news visualizations 12 pairwise correlations 199 process numbers in news 178–80 rational and emotional responses of 11 regression analysis 198 using data visualizations 197–9 news coverage of poverty 63 political communication of statistics news industries and journalism scholarship 201 news issues numbers and public perception of 180–1 problem with numbers 187 news on election 177 news production process 201 news reporting data journalism 33 false equivalence 34 impartiality 34 quantitative supply of statistics in 33–4 truth, the 34 newsroom 10 perspective for future 12 statistics in 10 web metrics into 10 newsroom, web metrics penetration into 116–20 audience channel 116 hierarchal regression analysis 119–20 in-house tracking software 117 interactive digital environment 116 radical transformation 119 third-party software 117 types of metrics-driven editorial adjustment 118 user’s IP address 116 news values 228 news website 192 Dutch news website 187 economic section on 177 New York Times, The 136 next generation data (analysis) journalism 234–7 data journalism courses 235 distribution of ‘fake news’ 234 improving journalism education 237 integration of journalism with statistics 236 interactive (data-based) reporting 235 interdisciplinary teaching 238 international cooperation with many journalists 234 journalism skills, teaching 236 journalistic thinking 236 knowledge-tested reporting 237 professionalizing data literacy 237 science journalism programme 236 non-news professionals non-profit Fact Check 24 ‘normal’ (statistical term) 21 Norway 268 ‘nothing-but-the-fact’ journalism 187 NRC Handelsblad (Dutch newspaper) 195 NU.nl (online news site in the Netherlands) 195 number paradox 11 numbers 133 -based stories and emotion 133 digital age of journalism 227 and figures 227–28 Guinness Book of World Records principle 227 in modern life 2–3 and perceived credibility of news 182–5 power of 134–5 and public perception of news issues 180–1 as rhetorical device 181–2 and statistics Numbers and Nerves (Slovic and Slovic) 141 number use to enhance credibility 183–5 function of ethos 182 journalism-as-information-model 182 by journalists, reasons 181–2 Index numerically versus non-numerically based news 138–40 advantage of experimental study 139 fact-based news story 139 quantifiable information 138 Obama, Barack (US president) 47, 48 and al-Qaeda 49 killing Americans abroad 51 rejecting counterinsurgency doctrine 48–9 objective economic models 64 objective reporting 67 official sources, over-reliance on 70–3 ‘economizing’ poverty 73 pro-globalization approaches 71 to underpin ‘truth’ 70 O Globo (Brazil) 79 Omniture (third-party software) 117 Ophan, in-house tracking software at Guardian 117 opinion polling 53 Organisation for Economic Development and Co-Operation (OECD) 157, 243 over-reliance of office sources 70–3 Panama Papers 68 Pearson correlation coefficient 140 perceived credibility of news and numbers 182–7 coral found 185 demo record McCartney 185 suicide attacks Yemen 185 Periodic International Student Assessment (PISA) 243 personification combining with statistics 136–38 and statistical information 141 Philly.com 123 point-biserial correlation 22 Point IV Programme 64 political communication of statistics Politico.com 123 Poverty Alliance 72 Poverty and Shared Prosperity (World Bank publication) 69 285 poverty statistics 63–4 flaws in validity and reliability 68 humanitarian–neo-liberal ideology 69 news beat 67 ‘objective’ assessment 67 plurality of poverty concept 65 symptoms of poverty 66 poverty threshold precision journalism 231, 269 presentation formats 166–8 conditional probability reasoning 167 decision-making tasks 167 effects on issue perception 168 journalists, selection of method 166 numeric and visual presentation 167 numeric information presentation 167 percentages 167 visually displayed information, disadvantages of 168 Program for International Assessment of Adult Competencies (PIAAC) 157 Pro Publica (investigative journalism organization) 97, 109 psychic numbing and compassion fatigue 135–6 Kristof ’s approach to 136–8 psychophysical numbing 10, 133 public communicators, statistical information implications 171–3 avoiding reading online content 173 cognizance 173 discomfort with computational tasks 171 effects of exemplar aggregation 172 practical strategies 172 presenting numeric information 171 processing health-related numeric information 173 Public Opinion (Lippmann) qualitative results, concepts of p-value 21 quantitative data 10 quantitative depictions of threatening trends correcting base rate neglect 155–7 frequency versus rate data 149–53 scope of problem 153–5 quantitative literacy 157, 164 286 quantitative trends 154 see also quantitative depictions of threatening trends quantitative turn in journalism Quartz (news organization) 126 ‘random’ (statistical term) 21 reasoning 10 using numerical data 246 see also statistical reasoning research questions 245 rethinking impartiality 44–5 challenging statistical references 45 government’s statistical claims 44 rituals of objectivity and bias 49–51 drone war failure 51 notion of ‘objectivity’ 50 numbers and precision 49 process of ‘calculative practices’ 51 quantification 50 statistics for ending conflict 50 science and economy 230–1 crosschecking scientific data 230 existing quality criteria in science journalism 231 skills of science journalists 231 science communication 81 science establishment lay public voice in 83 science across to lay public 81 science journalism 9, 78–9, 230 crosschecking scientific data 230 and data-driven journalism 231–3 be an exception 80–4 existing quality criteria 231 help lay publics to understand 86–7, 89 precision journalism 231 science statistics relevant to lay publics 85–6 skills of science journalists 231 Science Media Centre 214 science reporting cruciality of numbers 80 high education level 81 presenting science 83 Index reasons for omission of methodological information 88–9 reporting of statistical data in 84 to understand and appreciate science 83 science statistics 84 help lay publics to understand 86–7 relevant to lay public 85–6 Scottish Government report 72 second generation data journalism 13, 226 Second Intifada 47 self-reported emotions, shortcomings of 140 signal/noise ratio 160 ‘significant’ (statistical term) 21 SMI EyeTracking Glasses (ETG) 196 Smith, Owen (Labour) 41–2 Social Justice Ireland (SJI) 72 social legitimacy 271 social network analysis (SNA) 56 social science research ethics 266 social world 260 Society of Investigative Reporters and Editors (IRE) in the United States 232 sociotechnical phenomenon 260 sport pages 211 statistical bullshit 4–5 bullshitter and liar ‘chicken and egg’ relationship statistical distortions, individual and social consequences of 157–9 generalized anxiety disorder (GAD) 158 misperception of risk 159 paternalistic ‘protectors’ of the public 159 threat-related stories 158 undesirable effects 158 statistical information, 6, 32, 35, 39, 44, 170 in content analysis data 84 experimental psychology research 133 on poverty 74 presentation format 166–8 in sport pages 211 translating to news 19 Index verification 24 see also journalists, statistical information implications statistical interpretation xvi experimental psychology research 133 quality of Statistical Package for the Social Sciences (SPSS) 247, 250, 257 statistical popularization books 27 statistical reasoning 243–4 availability heuristic 244 data-gathering efforts 256 faculty entrepreneurs, role of 252–3 future of 253–6 not offered in major 248–9 raison d’etre 255 representativeness heuristic 244 statistical reasoning skills 244 structural factors facilitating 249–50 statistical reporting 84, 90, 133, 223 statistical skills of everyday journalists 229–30 ‘natural’ problem zone for journalism 229 Statistical Society of London 212–13 statistical thinking 19 core concept of 20 statistical training 6, 8, 13, 20, 27, 79, 242 profession-centric 256 statisticians 209 and media processes 214–16 seeing news processes 210 stereotypical views 222 working with journalists, advice for 222–3 statistics common misuses 20–3 definition by Best 182 effective representation of 78 Euro-barometer Evaluation 184 and media 210–14 in nature of reporting 221–2 and public 220–2 –society relationship with and without numbers 183 Stela, in-house tracking software at New York Times 117 287 story framing, definition 135 strategic ritual of objectivity Structural Adjustments Programmes (SAPs) 64 structural equation modelling (SEM) programme 247 survey results 211 Sweden 268 tax credits system, reporting changes to 38–9 broadcast media role 39 exploiting availability of statistics 42–4 National Minimum Wage (NMW) 39 rejecting proposed changes 39 tit-for-tat statistical claims 41–2 using independent statistics to challenge claims 39–41 Terror Free Tomorrow (TFT) 57 Thatcher, Margaret 62 Tiger that Isn’t, The (Blastland and Dilnot) 217 Times, The 79 traditional gatekeeping, powerless news audience in 114–16 audience-driven approach 115 five-level model of 114 German news output, comparison 115 to journalism scholarship 114 traditional news journalism 269 and data journalism 271 Transactions of the Statistical Society of London (Robertson) 213 Trouw (Dutch newspaper) 195 UK news media 34–5 case study 35–8 common source of statistics 35 data about crime and terror 34 scrutinizing statistics 35 UK Statistics Authority 45 unmanned aerial vehicles (UAV) 47 US Bureau of National Statistics 68 US National Security Agency (US NSA) 56 288 VandeHei, Jim 123 Venezuela 62–3 Viner, Katherine (editor-in-chief of The Guardian) 25 visualization elements 97, 104, 106–7, 110 visualizations in news 192, 195–6 attention-catcher 195 attention to 193 determinants of 194 eye-tracking method 193, 196 focus groups 196 influencing appreciation 200 information processer 195 interactive visualizations 194 navigation through visualization 195 reader connect the text with 195 survey 196–7 use of 193 visualization software 194 visual numeric information 181 Visual Revenue (third-party software) 117 Volkswagen Foundation 238 Wall Street Journal 126–7 War on Terror 48 Washington Post 57 downsizing news team 122 respecting Monkey Cage blog 52 Truth Teller prototype 270 The Wealth of Nations (Poovey) 212 Index web metrics 113 metrics-driven audience agenda 120–4 penetration into newsroom 116–20 (see also newsroom, web metrics penetration into) websites news 116 instructional websites 242 news on 193 professional (Dutch) news websites 185 text versus graphics 193 Wei, Sisi (news app developer) Wells, Herbert G. WikiLeaks documents 33 workforce lack of arithmetic skill 178 unemployed 160 World Bank 66 to delineate developing and developed countries 72 developing countries 71 The Guardian news 69 official statistics on poverty 71 World Health Organization (WHO) 218 World Wide Web 2, 231 XKCD (web comic strip) 219 Yusufzai, Malala (victim of Taliban terror) 58 Zika virus news 164 .. .News, Numbers and Public Opinion in a Data- Driven World ii News, Numbers and Public Opinion in a Data- Driven World Edited by An Nguyen Bloomsbury Academic An imprint of Bloomsbury Publishing... social world, to make rational choices over public affairs and ultimately to maintain their influence over public institutions 4 News, Numbers and Public Opinion in a Data- Driven World The age... the News, Numbers and Public Opinion in a Data- Driven World world’s move to transparency and open-access data in the digital environment and the recent introduction of simple, user-friendly data