Editing Media bias (section)

== Types ==
In the 2017 Oxford Handbook of Political Communication, S. Robert Lichter described how in academic circles, media bias is more of a hypothesis to explain various patterns in news coverage than any fully-elaborated theory,<ref name=":1" /> and that a variety of potentially overlapping types of bias have been proposed that remain widely debated.

Various proposed hypotheses of media bias have included:
* [[Advertising]] bias, when stories are selected or slanted to please advertisers.<ref>{{cite journal|last1=Eberl|first1=Jakob-Moritz|last2=Wagner|first2=Markus|last3=Boomgaarden|first3=Hajo G.|year=2018|title=Party Advertising in Newspapers|journal=Journalism Studies|volume=19|issue=6|pages=782–802|doi=10.1080/1461670X.2016.1234356|s2cid=151663981}}</ref>
* Anti-science bias, when stories promote superstition or other non-scientific ideas.<ref name=":6" />
* [[Concision]] bias, a tendency to report views that can be summarized succinctly, crowding out more unconventional views that take time to explain.{{Citation needed|date=March 2024}}
* Content bias, differential treatment of the parties in political conflicts, where biased news presents only one side of the conflict.<ref name=":2">{{Cite journal|last=Entman|first=Robert M.|date=2007|title=Framing Bias: Media in the Distribution of Power|url=https://academic.oup.com/joc/article/57/1/163-173/4102665|journal=Journal of Communication|language=en|volume=57|issue=1|pages=163–173|doi=10.1111/j.1460-2466.2006.00336.x|s2cid=43280110 }}</ref>
* Corporate bias, when stories are selected or slanted to please corporate owners of media.<ref>{{Cite journal |last1=Kedia |first1=Simi |last2=Kim |first2=Gunchang |date=2021 |title=Impact of Media Ownership on News Coverage |url=https://www.ssrn.com/abstract=3773240 |journal=SSRN Electronic Journal |language=en |doi=10.2139/ssrn.3773240 |issn=1556-5068}}</ref><ref>{{Cite journal |last1=Kedia |first1=Simi |last2=Kim |first2=Gunchang |date=5 Mar 2021 |title=Impact of Media Ownership on News Coverage |url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3773240 |journal=Forthcoming Management Science|ssrn=3773240 }}</ref>
* Coverage bias<ref name=":0">{{cite journal |last1=Eberl |first1=J.-M. |last2=Boomgaarden |first2=H. G. |last3=Wagner |first3=M. |date=2015-11-19 |title=One Bias Fits All? Three Types of Media Bias and Their Effects on Party Preferences |journal=Communication Research |language=en |volume=44 |issue=8 |pages=1125–1148 |doi=10.1177/0093650215614364 |s2cid=1574634}}</ref> when media choose to report only negative news about one party or ideology<ref name=":8">{{cite journal |last1=D'Alessio |first1=D |last2=Allen |first2=M |date=2000-12-01 |title=Media bias in presidential elections: a meta-analysis |journal=Journal of Communication |language=en |volume=50 |issue=4 |pages=133–156 |doi=10.1111/j.1460-2466.2000.tb02866.x |issn=1460-2466}}</ref>
* Decision-making bias, means that the motivation, frame of mind, or beliefs of the journalists will have an impact on their writing. It is generally pejorative.<ref name=":2" />
* Demand-driven bias.<ref name=":5" />
* Demographic bias, where factors such as gender, race, and social and economic status influence reporting<ref>{{Cite journal |title=Media Bias Monitor: Quantifying Biases of Social Media News Outlets at Large-Scale |url=https://people.mpi-sws.org/~babaei/icwsm_2018.pdf |journal=Proceedings of the Twelfth International AAAI Conference on Web and Social Media (ICWSM 2018)}}</ref> and can be a factor in different coverage of various demographic groups.<ref>{{cite journal |last1=van der Pas |first1=Daphne J. |date=10 November 2022 |title=Do European media ignore female politicians? A comparative analysis of MP visibility |journal=West European Politics |volume=45 |issue=7 |pages=1481–1492 |doi=10.1080/01402382.2021.1988387 |s2cid=244550876 |hdl-access=free |hdl=11245.1/f63f3114-d170-40c3-aeae-c6e14259999c}}</ref><ref name="Shor">{{cite journal |last1=Shor |first1=Eran |last2=van de Rijt |first2=Arnout |last3=Fotouhi |first3=Babak |date=2019 |title=A Large-Scale Test of Gender Bias in the Media |url=https://sociologicalscience.com/download/vol-6/september/SocSci_v6_526to550.pdf |journal=Sociological Science |volume=6 |pages=526–550 |doi=10.15195/v6.a20 |s2cid=202625899 |access-date=7 June 2023}}</ref>
* Distortion bias, when the fact or reality is distorted or fabricated in the news.<ref name=":2" />
* Episodic framing of television, for example, can lead people to ascribe blame to individuals instead of society, in contrast to thematic framing that leads people to look more at societal causes.<ref>{{Cite book |last=Iyengar |first=Shanto |title=Is anyone responsible? how television frames political issues |date=1994 |publisher=Univ. of Chicago Press |isbn=978-0-226-38855-7 |series=American Politics and Political Economy Series |location=Chicago}}</ref>
* [[False balance]] and [[false equivalence]] occur when an issue is presented as having equally-compelling reasons on both sides, despite disproportionate amounts of evidence favoring one (also known as undue weight).{{Citation needed|date=March 2024}}
* False [[timeliness]], implying that an event is a new event, and thus deriving notability, without addressing past events of the same kind.{{Citation needed|date=March 2024}}
* [[Gatekeeping (communication)|Gatekeeping bias]] (also known as selectivity<ref>{{Cite journal |last1=Hofstetter |first1=C. Richard |last2=Buss |first2=Terry F. |date=1978-09-01 |title=Bias in television news coverage of political events: A methodological analysis |journal=Journal of Broadcasting |volume=22 |issue=4 |pages=517–530 |doi=10.1080/08838157809363907 |issn=0021-938X}}</ref> or selection bias),<ref name="Groeling">{{cite journal |last=Groeling |first=Tim |date=2013-05-10 |title=Media Bias by the Numbers: Challenges and Opportunities in the Empirical Study of Partisan News |journal=Annual Review of Political Science |language=en |volume=16 |issue=1 |pages=129–151 |doi=10.1146/annurev-polisci-040811-115123 |doi-access=free}}</ref> when stories are selected or deselected, sometimes on ideological grounds (see [[Spike (journalism)|spike]]).<ref name=":8" /> It is sometimes also referred to as agenda bias, when the focus is on political actors and whether they are covered based on their preferred policy issues.<ref name=":0" /><ref>{{cite journal |last=Brandenburg |first=Heinz |date=2006-07-01 |title=Party Strategy and Media Bias: A Quantitative Analysis of the 2005 UK Election Campaign |journal=Journal of Elections, Public Opinion and Parties |volume=16 |issue=2 |pages=157–178 |doi=10.1080/13689880600716027 |issn=1745-7289 |s2cid=145148296}}</ref>
* [[Mainstream bias]], a tendency to report what everyone else is reporting, and to avoid stories that will offend anyone. This type of bias can result in the homogenization of information, diminishing diversity in media content and negatively impacting both media consumption and the overall user experience.<ref>{{Cite book |last1=Pan |first1=Jinhao |last2=Zhu |first2=Ziwei |last3=Wang |first3=Jianling |last4=Lin |first4=Allen |last5=Caverlee |first5=James |chapter=Countering Mainstream Bias via End-to-End Adaptive Local Learning |series=Lecture Notes in Computer Science |date=2024 |volume=14612 |editor-last=Goharian |editor-first=Nazli |editor2-last=Tonellotto |editor2-first=Nicola |editor3-last=He |editor3-first=Yulan |editor4-last=Lipani |editor4-first=Aldo |editor5-last=McDonald |editor5-first=Graham |editor6-last=Macdonald |editor6-first=Craig |editor7-last=Ounis |editor7-first=Iadh |title=Advances in Information Retrieval |chapter-url=https://link.springer.com/chapter/10.1007/978-3-031-56069-9_6 |language=en |location=Cham |publisher=Springer Nature Switzerland |pages=75–89 |doi=10.1007/978-3-031-56069-9_6 |isbn=978-3-031-56069-9}}</ref>
* [[Negativity bias]] (or bad news bias), a tendency to show negative events and portray politics as less of a debate on policy and more of a zero-sum struggle for power. Excessive criticism or negativity can lead to cynicism and disengagement from politics.<ref>{{Cite book |last=Lichter |first=S. Robert |url=http://oxfordhandbooks.com/view/10.1093/oxfordhb/9780199793471.001.0001/oxfordhb-9780199793471-e-44 |title=Theories of Media Bias |date=2014-09-02 |publisher=Oxford University Press |editor-last=Kenski |editor-first=Kate |volume=1 |pages=403, 410–412 |language=en |doi=10.1093/oxfordhb/9780199793471.013.44 |isbn=978-0-19-979347-1 |editor-last2=Jamieson |editor-first2=Kathleen Hall}}</ref>
* Partisan bias, a tendency to report to serve particular political party leaning.<ref>{{cite journal|last1=Haselmayer|first1=Martin|last2=Wagner|first2=Markus|last3=Meyer|first3=Thomas M.|date=6 February 2017|title=Partisan Bias in Message Selection: Media Gatekeeping of Party Press Releases|journal=Political Communication|volume=34|issue=3|pages=367–384|doi=10.1080/10584609.2016.1265619|pmc=5679709|pmid=29170614}}</ref>
* [[Sensationalism]], bias in favor of the exceptional over the ordinary, giving the impression that rare events, such as airplane crashes, are more common than common events, such as automobile crashes. "[[Hierarchy of death]]" and "[[missing white woman syndrome]]" are examples of this phenomenon.
* Speculative content, when stories focus not on what has occurred, but primarily on what might occur, using words like "could", "might", or "what if", without labeling the article as analysis or opinion.<ref>{{Cite journal |last1=Brand |first1=Ann-Kathrin |last2=Meyerhoff |first2=Hauke S. |last3=Holl |first3=Florian |last4=Scholl |first4=Annika |date=March 2023 |title=When linguistic uncertainty spreads across pieces of information: Remembering facts on the news as speculation |url=https://doi.apa.org/doi/10.1037/xap0000428 |journal=[[Journal of Experimental Psychology: Applied]] |language=en |volume=29 |issue=1 |pages=18–31 |doi=10.1037/xap0000428 |pmid=35786942 |issn=1939-2192 }}</ref>
* Statement bias (also known as tonality bias<ref name=":0" /> or presentation bias),<ref name="Groeling" /> when media coverage is slanted towards or against particular actors or issues.<ref name=":8" />
* Structural bias, when an actor or issue receives more or less favorable coverage as a result of [[News values|newsworthiness]] and media routines, not as the result of ideological decisions<ref>{{cite journal |last1=Haselmayer |first1=Martin |last2=Meyer |first2=Thomas M. |last3=Wagner |first3=Markus |year=2019 |title=Fighting for attention: Media coverage of negative campaign messages |journal=Party Politics |volume=25 |issue=3 |pages=412–423 |doi=10.1177/1354068817724174 |s2cid=148843480}}</ref><ref>{{cite journal |last=van Dalen |first=A. |date=2011-06-10 |title=Structural Bias in Cross-National Perspective: How Political Systems and Journalism Cultures Influence Government Dominance in the News |journal=The International Journal of Press/Politics |language=en |volume=17 |issue=1 |pages=32–55 |doi=10.1177/1940161211411087 |s2cid=220655744}}</ref> (e.g. [[Incumbent|incumbency bonus]]).
* Supply-driven bias<ref name=":5" />
* [[Tuchman's Law]] suggests how people overestimate the risk from dangers that are disproportionately discussed in media.
* Ventriloquism, when experts or witnesses are quoted in a way that intentionally voices the author's own opinion.{{Citation needed|date=March 2024}}

An ongoing and unpublished research project named "The Media Bias Taxonomy" is attempting to assess the various definitions and meanings of media bias. While still ongoing, it attempts to summarize the domain as the distinct subcategories linguistic bias (encompassing linguistic intergroup bias, framing bias, epistemological bias, bias by semantic properties, and connotation bias), text-level context bias (featuring statement bias, phrasing bias, and spin bias), reporting-level context bias (highlighting selection bias, coverage bias, and proximity bias), cognitive biases (such as selective exposure and partisan bias), and related concepts like [[Framing (social sciences)|framing]] effects, hate speech, sentiment analysis, and group biases (encompassing gender bias, racial bias, and religion bias). The authors emphasize the complex nature of detecting and mitigating bias across different media content and contexts.<ref>{{cite arXiv |last1=Spinde |first1=Timo |last2=Hinterreiter |first2=Smilla |last3=Haak |first3=Fabian |last4=Ruas |first4=Terry |last5=Giese |first5=Helge |last6=Meuschke |first6=Norman |last7=Gipp |first7=Bela |date=2023-01-01 |title=The Media Bias Taxonomy: A Systematic Literature Review on the Forms and Automated Detection of Media Bias |class=cs.CL |eprint=2312.16148}} [https://media-bias-research.org/wp-content/uploads/2023/12/spinde2023.pdf additional copy]</ref>{{Better source needed|reason=The current source is insufficiently reliable ([[WP:NOTRS]]). This is a pre-print and has not been peer-reviewed - please update with the final published paper|date=March 2024}}