Increasing and Decreasing Perceived Bias by Distorting the Quality of News Website Design

News website design has previously been shown to impact perceived credibility, and one of its core dimensions and measures, bias. This paper demonstrates that by adapting the quality of the visual presentation of webpages from nine of the most popular news websites, to reflect high quality and low quality news agencies, we can predicatively increase or decrease perceived bias in the news articles they contain. This effect was common across the websites of traditional print, news magazine, and international news agencies, and across articles with different levels of bias. The distortions focused on the visual quality of a websites’ design, including the amount, size, and prominence of advertising, news article meta data, supporting material, gaudy calls to action, and the percentage of the webpage dedicated to the news article. Higher quality visual experiences reflecting quality news agencies were shown to reduce bias, while those with a low quality visual experience reflecting less professional news agencies increased bias. Significant differences were also found between low and high quality designs showing the same news articles. This paper reports results on one part of a large study on the impact of visual appearance and design on the perception of bias in online news.

Content

Author and article information

Contributors

Brendan Spillane

Séamus Lawless

Vincent Wade

Conference

Publication date: July 2018

Publication date (Print): July 2018

Pages: 1-13

Affiliations

[1 ] ADAPT Centre, Trinity College Dublin, Ireland

Article

DOI: 10.14236/ewic/HCI2018.61

SO-VID: cb12f439-3c3a-4732-b894-30186c1f61df

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This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: Proceedings of the 32nd International BCS Human Computer Interaction Conference

Conference acronym: HCI

Conference number: 32

Conference location: Belfast, UK

Conference date: 4 - 6 July 2018

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: Human Computer Interaction Conference

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1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/HCI2018.61

Self URI (journal page): https://ewic.bcs.org/

REFERENCES

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A. BleierM. Eisenbeiss 2015 Personalized Online Advertising Effectiveness: The Interplay of What, When, and Where Mark. Sci http://doi.org/10.1287/mksc.2015.0930
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S. Chaiken 1980 Heuristic Versus Systematic Information Processing and the Use of Source Versus Message Cues in Persuasion J. Pers. Soc. Psychol 39 752 766
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J.E. CookS.Z. Attari 2012 Paying for What Was Free: Lessons from the New York Times Paywall Cyberpsychology Behav. Soc. Netw 15 682 687 http://doi.org/10.1089/cyber.2012.0251
L. Cooke 2005 A visual convergence of print, television, and the internet: charting 40 years of design change in news presentation New Media Soc 7 22 46 http://doi.org/10.1177/1461444805049141
J. EarlA. MartinJ.D. McCarthyS.A. Soule 2004 The Use of Newspaper Data in the Study of Collective Action Annu. Rev. Sociol 30 65 80
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V. LarcineseR. Puglisi, Snyder J.M. Jr 2011 Partisan bias in economic news: Evidence on the agenda-setting behavior of US newspapers. J. Public Econ 95 1178 1189
M.A. Lee 1991 Unreliable sources: A guide to detecting bias in news media Lyle Stuart
D.T. Lowry 1973 Measures of Network News Bias in the 1972 Presidential Campaign J. Broadcast 18 387
D.T. LowryJ.A. Shidler 1998 The Sound Bites, the Biters, and the Bitten: A Two-Campaign Test of the Anti-Incumbent Bias Hypothesis in Network TV News Journal. Mass Commun. Q 75 719 729 http://doi.org/10.1177/107769909807500407
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Q. MaM. Yoshikawa Q. LiL. FengJ. PeiS.X. WangX. ZhouQ.-M Zhu 2009 Topic and Viewpoint Extraction for Diversity and Bias Analysis of News Contents Advances in Data and Web Management, Lecture Notes in Computer Science Springer Berlin Heidelberg 150 161 http://doi.org/10.1007/978-3-642-00672-2_15
D. McQuail 1992 Media performance: Mass communication and the public interest Sage
M.J. Metzger 2007 Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research J. Am. Soc. Inf. Sci. Technol 58 2078 2091 http://doi.org/10.1002/asi.20672
M.J. MetzgerA.J. Flanagin 2015 Psychological Approaches to Credibility Assessment Online
A. Mitchell 2015 Pew Research Center April 2015 State of the News Media 2015. Pew Res. Cent. Journal. Proj
P.M. Napoli 2014 On Automation in Media Industries: Integrating Algorithmic Media Production into Media Industries Scholarship Media Ind. J. 1 http://dx.doi.org/10.3998/mij.15031809.0001.107
P.M. Napoli 2013 The Algorithm as Institution: Toward a Theoretical Framework for Automated Media Production and Consumption
R.E. PettyJ.T. Cacioppo 1986 The Elaboration Likelihood Model of Persuasion, in: Communication and Persuasion, Springer Series in Social Psychology Springer New York 1 24
E. PujolO. HohlfeldA. Feldmann 2015 Annoyed Users: Ads and Ad-Block Usage in the Wild, in: Proceedings of the 2015 Internet Measurement Conference, IMC ’15 ACM New York, NY, USA 93 106 http://doi.org/10.1145/2815675.2815705
S.A. RainsC.D. Karmikel 2009 Health information-seeking and perceptions of website credibility: Examining Web-use orientation, message characteristics, and structural features of websites Comput. Hum. Behav., Including the Special Issue: State of the Art Research into Cognitive Load Theory 25 544 553 http://doi.org/10.1016/j.chb.2008.11.005
M. RecasensC. Danescu-Niculescu-MizilD. Jurafsky 2013 Linguistic Models for Analyzing and Detecting Biased Language in: ACL (1) 1650 1659
J.E. RichardsonJ. Stanyer 2011 Reader opinion in the digital age: Tabloid and broadsheet newspaper websites and the exercise of political voice Journalism 12 983 1003 http://doi.org/10.1177/1464884911415974
S.Y. Rieh 2002 Judgment of Information Quality and Cognitive Authority in the Web J. Am. Soc. Inf. Sci. Technol 53 145 161
S.Y. RiehB. Hilligoss 2008 College students’ credibility judgments in the information-seeking process Digit. Media Youth Credibil 49 72
D. RobinsJ. Holmes 2008 Aesthetics and credibility in web site design Inf. Process. Manag., Evaluation of Interactive Information Retrieval Systems 44 386 399 http://doi.org/10.1016/j.ipm.2007.02.003
W. SchneiderR. Shiffrin 1977 Controlled and automatic human information processing: I. Detection, search, and attention 84, 1 66 http://doi.org/10.1037/0033-295X.84.1.1
R.M. ShiffrinW. Schneider 1977 Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory Psychol. Rev 84 127 190 http://doi.org/10.1037/0033-295X.84.2.127
H. Sjøvaag 2016 Introducing the Paywall Journal. Pract 10 304 322 http://doi.org/10.1080/17512786.2015.1017595
B. SpillaneS. LawlessV. Wade 2017a Perception of Bias: The Impact of User Characteristics, Website Design and Technical Features, in: Proceedings of the International Conference on Web Intelligence, WI ’17 ACM New York, NY, USA 227 236 http://doi.org/10.1145/3106426.3106474
B. SpillaneS. LawlessV. Wade 2017b Measuring Bias in News Websites, Towards a Model for Personalization, in: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, UMAP ’17 ACM New York, NY, USA 387 388 http://doi.org/10.1145/3079628.3079647
R.L. StevensonR.A. EisingerB.M. FeinbergA.B. Kotok 1973 Untwisting the news twisters: A replication of Efron’s study Journal. Q 50 211 219
R.L. StevensonM.T. Greene 1980 A Reconsideration of Bias in the News Journal. Q 57 115 121 http://doi.org/10.1177/107769908005700117
S.S. Sundar 2008 The MAIN model: A heuristic approach to understanding technology effects on credibility Digit. Media Youth Credibil 73 100
S.S. SundarS. Knobloch-WesterwickM.R. Hastall 2007 News cues: Information scent and cognitive heuristics J. Am. Soc. Inf. Sci. Technol 58 366 378 http://doi.org/10.1002/asi.20511
N. ThurmanS. Schifferes 2012 The Future of Personalization at News Websites: Lessons from a longitudinal study Journal. Stud 13 775 790 http://doi.org/10.1080/1461670X.2012.664341
C.N. WathenJ. Burkell 2001 Believe it or not: Factors influencing credibility on the Web J. Am. Soc. Inf. Sci. Technol 53 134 144
R.F. YalchR. Elmore-Yalch 1984 The Effect of Numbers on the Route to Persuasion J. Consum. Res 11 522 527
P. ZhangG.M. von Dran 2000 Satisfiers and dissatisfiers: A two-factor model for website design and evaluation J. Am. Soc. Inf. Sci 51 1253 1268 http://doi.org/10.1002/1097-4571(2000)9999:99993.0.CO;2-O

Comments

Comment on this article

[1] C.D. AllportJ.A. Pendley 2010 The impact of website design on the perceived credibility of internet financial reporting Intell. Syst. Account. Finance Manag. 17 127 141 http://doi.org/10.1002/isaf.318

[2] P. Bakker 2012 Aggregation, Content Farms and Huffinization Journal. Pract. 6 627 637 http://doi.org/10.1080/17512786.2012.667266

[3] A. BalahurR. SteinbergerE. Goot van derB. PouliquenM. Kabadjov 2009 Opinion Mining on Newspaper Quotations, in: IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, 2009 WI-IAT ’09. Presented at the IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies 2009 WI-IAT ’09523526 http://doi.org/10.1109/WI-IAT.2009.340

[4] J. Bar-IlanK. KeenoyM. LeveneE. Yaari 2009 Presentation bias is significant in determining user preference for search results—A user study J. Am. Soc. Inf. Sci. Technol 60 135 149 http://doi.org/10.1002/asi.20941

[5] A. BleierM. Eisenbeiss 2015 Personalized Online Advertising Effectiveness: The Interplay of What, When, and Where Mark. Sci http://doi.org/10.1287/mksc.2015.0930

[6] C. BudakS. GoelJ.M. Rao 2016 Fair and Balanced? Quantifying Media Bias through Crowdsourced Content Analysis Public Opin. Q. 80 250 271 http://doi.org/10.1093/poq/nfw007

[7] S. Chaiken 1980 Heuristic Versus Systematic Information Processing and the Use of Source Versus Message Cues in Persuasion J. Pers. Soc. Psychol 39 752 766

[8] C.J. ChungY. NamM.A. Stefanone 2012 Exploring Online News Credibility: The Relative Influence of Traditional and Technological Factors J. Comput.-Mediat. Commun 17 171 186 http://doi.org/10.1111/j.1083-6101.2011.01565.x

[9] J.E. CookS.Z. Attari 2012 Paying for What Was Free: Lessons from the New York Times Paywall Cyberpsychology Behav. Soc. Netw 15 682 687 http://doi.org/10.1089/cyber.2012.0251

[10] L. Cooke 2005 A visual convergence of print, television, and the internet: charting 40 years of design change in news presentation New Media Soc 7 22 46 http://doi.org/10.1177/1461444805049141

[11] J. EarlA. MartinJ.D. McCarthyS.A. Soule 2004 The Use of Newspaper Data in the Study of Collective Action Annu. Rev. Sociol 30 65 80

[12] E. Efron 1971 The News Twisters Nash Pub, Los Angeles

[13] F. FicoJ.D. RichardsonS.M. Edwards 2004 Influence of Story Structure on Perceived Story Bias and News Organization Credibility Mass Commun. Soc 7 301 318 http://doi.org/10.1207/s15327825mcs0703_3

[14] A.J. FlanaginM.J. Metzger 2007 The role of site features, user attributes, and information verification behaviors on the perceived credibility of web-based information New Media Soc 9 319 342 http://doi.org/10.1177/1461444807075015

[15] B.J. Fogg 2003 Prominence-interpretation theory: explaining how people assess credibility online, in: CHI ’03 Extended Abstracts on Human Factors in Computing Systems, CHI EA ’03 ACM, New York, NY, USA 722 723 http://doi.org/10.1145/765891.765951

[16] B.J. FoggC. SoohooD.R. DanielsonL. MarableJ. StanfordE.R. Tauber 2003 How do users evaluate the credibility of Web sites?: a study with over 2,500 participants, in: Proceedings of the 2003 Conference on Designing for User Experiences 1 15

[17] B.J. FoggH. Tseng 1999 The Elements of Computer Credibility, in: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’99 ACM, New York, NY, USA 80 87 http://doi.org/10.1145/302979.303001

[18] H.S. FriedmanT.I. MertzM.R. DiMatteo 1980 Perceived Bias in the Facial Expressions of Television News Broadcasters J. Commun 30 103 111 http://doi.org/10.1111/j.1460-2466.1980.tb02022.x

[19] J.W. FritchR.L. Cromwell 2001 Evaluating Internet resources: Identity, affiliation, and cognitive authority in a networked world J. Am. Soc. Inf. Sci. Technol 52 499 507 http://doi.org/10.1002/asi.1081

[20] B.W. Gorham 2006 News Media’s Relationship with Stereotyping: The Linguistic Intergroup Bias in Response to Crime News J. Commun 56 289 308 http://doi.org/10.1111/j.1460-2466.2006.00020.x

[21] T. Groeling 2013 Media Bias by the Numbers: Challenges and Opportunities in the Empirical Study of Partisan News Annu. Rev. Polit. Sci 16 129 151 http://doi.org/10.1146/annurev-polisci-040811-115123

[22] T. GrosecloseJ. Milyo 2005 A Measure of Media Bias Q. J. Econ 120 1191 1237 http://doi.org/10.1162/003355305775097542

[23] B. HilligossS.Y. Rieh 2008 Developing a unifying framework of credibility assessment: Construct, heuristics, and interaction in context Inf. Process. Manag 44 1467 1484

[24] W.S. JungM. Chung-Y., E.S. Rhee 2017 The Effects of Attractiveness and Source Expertise on Online Health Sites Health Commun 0 1 10 http://doi.org/10.1080/10410236.2017.1323364

[25] V. KumarB. AnandS. GuptaF. Oberholzer-Gee 2012 The New York Times Paywall

[26] V. LarcineseR. Puglisi, Snyder J.M. Jr 2011 Partisan bias in economic news: Evidence on the agenda-setting behavior of US newspapers. J. Public Econ 95 1178 1189

[27] M.A. Lee 1991 Unreliable sources: A guide to detecting bias in news media Lyle Stuart

[28] D.T. Lowry 1973 Measures of Network News Bias in the 1972 Presidential Campaign J. Broadcast 18 387

[29] D.T. LowryJ.A. Shidler 1998 The Sound Bites, the Biters, and the Bitten: A Two-Campaign Test of the Anti-Incumbent Bias Hypothesis in Network TV News Journal. Mass Commun. Q 75 719 729 http://doi.org/10.1177/107769909807500407

[30] T. LucassenR. MuilwijkM.L. NoordzijJ.M. Schraagen 2013 Topic familiarity and information skills in online credibility evaluation Ju. Am. Soc. Inf. Sci. Technol 64 254 264 http://doi.org/10.1002/asi.22743

[31] Q. MaM. Yoshikawa Q. LiL. FengJ. PeiS.X. WangX. ZhouQ.-M Zhu 2009 Topic and Viewpoint Extraction for Diversity and Bias Analysis of News Contents Advances in Data and Web Management, Lecture Notes in Computer Science Springer Berlin Heidelberg 150 161 http://doi.org/10.1007/978-3-642-00672-2_15

[32] D. McQuail 1992 Media performance: Mass communication and the public interest Sage

[33] M.J. Metzger 2007 Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research J. Am. Soc. Inf. Sci. Technol 58 2078 2091 http://doi.org/10.1002/asi.20672

[34] M.J. MetzgerA.J. Flanagin 2015 Psychological Approaches to Credibility Assessment Online

[35] A. Mitchell 2015 Pew Research Center April 2015 State of the News Media 2015. Pew Res. Cent. Journal. Proj

[36] P.M. Napoli 2014 On Automation in Media Industries: Integrating Algorithmic Media Production into Media Industries Scholarship Media Ind. J. 1 http://dx.doi.org/10.3998/mij.15031809.0001.107

[37] P.M. Napoli 2013 The Algorithm as Institution: Toward a Theoretical Framework for Automated Media Production and Consumption

[38] R.E. PettyJ.T. Cacioppo 1986 The Elaboration Likelihood Model of Persuasion, in: Communication and Persuasion, Springer Series in Social Psychology Springer New York 1 24

[39] E. PujolO. HohlfeldA. Feldmann 2015 Annoyed Users: Ads and Ad-Block Usage in the Wild, in: Proceedings of the 2015 Internet Measurement Conference, IMC ’15 ACM New York, NY, USA 93 106 http://doi.org/10.1145/2815675.2815705

[40] S.A. RainsC.D. Karmikel 2009 Health information-seeking and perceptions of website credibility: Examining Web-use orientation, message characteristics, and structural features of websites Comput. Hum. Behav., Including the Special Issue: State of the Art Research into Cognitive Load Theory 25 544 553 http://doi.org/10.1016/j.chb.2008.11.005

[41] M. RecasensC. Danescu-Niculescu-MizilD. Jurafsky 2013 Linguistic Models for Analyzing and Detecting Biased Language in: ACL (1) 1650 1659

[42] J.E. RichardsonJ. Stanyer 2011 Reader opinion in the digital age: Tabloid and broadsheet newspaper websites and the exercise of political voice Journalism 12 983 1003 http://doi.org/10.1177/1464884911415974

[43] S.Y. Rieh 2002 Judgment of Information Quality and Cognitive Authority in the Web J. Am. Soc. Inf. Sci. Technol 53 145 161

[44] S.Y. RiehB. Hilligoss 2008 College students’ credibility judgments in the information-seeking process Digit. Media Youth Credibil 49 72

[45] D. RobinsJ. Holmes 2008 Aesthetics and credibility in web site design Inf. Process. Manag., Evaluation of Interactive Information Retrieval Systems 44 386 399 http://doi.org/10.1016/j.ipm.2007.02.003

[46] W. SchneiderR. Shiffrin 1977 Controlled and automatic human information processing: I. Detection, search, and attention 84, 1 66 http://doi.org/10.1037/0033-295X.84.1.1

[47] R.M. ShiffrinW. Schneider 1977 Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory Psychol. Rev 84 127 190 http://doi.org/10.1037/0033-295X.84.2.127

[48] H. Sjøvaag 2016 Introducing the Paywall Journal. Pract 10 304 322 http://doi.org/10.1080/17512786.2015.1017595

[49] B. SpillaneS. LawlessV. Wade 2017a Perception of Bias: The Impact of User Characteristics, Website Design and Technical Features, in: Proceedings of the International Conference on Web Intelligence, WI ’17 ACM New York, NY, USA 227 236 http://doi.org/10.1145/3106426.3106474

[50] B. SpillaneS. LawlessV. Wade 2017b Measuring Bias in News Websites, Towards a Model for Personalization, in: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, UMAP ’17 ACM New York, NY, USA 387 388 http://doi.org/10.1145/3079628.3079647

[51] R.L. StevensonR.A. EisingerB.M. FeinbergA.B. Kotok 1973 Untwisting the news twisters: A replication of Efron’s study Journal. Q 50 211 219

[52] R.L. StevensonM.T. Greene 1980 A Reconsideration of Bias in the News Journal. Q 57 115 121 http://doi.org/10.1177/107769908005700117

[53] S.S. Sundar 2008 The MAIN model: A heuristic approach to understanding technology effects on credibility Digit. Media Youth Credibil 73 100

[54] S.S. SundarS. Knobloch-WesterwickM.R. Hastall 2007 News cues: Information scent and cognitive heuristics J. Am. Soc. Inf. Sci. Technol 58 366 378 http://doi.org/10.1002/asi.20511

[55] N. ThurmanS. Schifferes 2012 The Future of Personalization at News Websites: Lessons from a longitudinal study Journal. Stud 13 775 790 http://doi.org/10.1080/1461670X.2012.664341

[56] C.N. WathenJ. Burkell 2001 Believe it or not: Factors influencing credibility on the Web J. Am. Soc. Inf. Sci. Technol 53 134 144

[57] R.F. YalchR. Elmore-Yalch 1984 The Effect of Numbers on the Route to Persuasion J. Consum. Res 11 522 527

[58] P. ZhangG.M. von Dran 2000 Satisfiers and dissatisfiers: A two-factor model for website design and evaluation J. Am. Soc. Inf. Sci 51 1253 1268 http://doi.org/10.1002/1097-4571(2000)9999:99993.0.CO;2-O

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