News, numbers and public opinion in a data driven world

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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relationship  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