1. Introduction
In 1983, 90% of the American media was owned by 50 companies, while in 2011 only six companies (General Electric, News Corp, Disney, Viacom, Time Warner, and CBS) owned the same 90% of the American media [
1]. Since the year 1900s, independent news media has become subject to more concentrated control. With fewer and more powerful players, ideological impact becomes a more prominent concern. Economies of scale, and possibly other factors, may enable individual players to impose their ideological views more fiercely, without being compromised by a plurality of multifarious other players. Reporting objectively, truthfully, and with ideologically neutrality, is challenging. Tribe [
2] suggests that tools in policy science are themselves ideologically biased. Levins [
3] and Nagy, Fairbrother, Etterson, and Orme-Zavaleta [
4] suggest that truth may emerge by intersecting independent lies. (That is, various independent models may together resemble truth.)
One widely reported controversial media scenario, which led to subsequent lawsuits, was between high school student Nicholas Sandmann from northern Kentucky Covington Catholic High School and the 64-year old native American Nathan Phillips at the Lincoln Memorial in Washington D.C., USA [
5,
6]. Sandmann wore a Make America Great Again hat and was in a group of fellow students on an annual school trip to attend the pro-life March for Life, combined with sightseeing. They waited for a bus to Kentucky. Phillips was beating a drum and chanting, while partaking in a group of Native American marchers attending the Indigenous Peoples March. Phillips was locking eyes with a smiling Sandmann a few inches apart. Early selective videos of the interaction on 18 January 2019 led most of the media to criticize Sandmann and the students for potentially provoking Phillips. It turned out that many videos and audio recordings of the interaction existed given the presence of many people at the prominent location. As accumulated and more full evidence of the interaction emerged, a view gradually arose that, potentially, the story was the opposite of that originally reported, and that Phillips was potentially provoking Sandmann. This remarkable turn of events caused the media to subsequently react in many different manners, hypothetically, in accordance with their ideological position. Examples of the media’s reactions, from one extreme to the other, were to retract and apologize, rewrite, reinterpret due to new evidence, ignore, retain the original account with some rewriting, or retain the original account with no adjustment.
Motivated by the potential ideological concerns of media organizations, and scenarios, such as the one sketched above, this article develops a model of the background where two adversarial actors interact controversially. The model is technically a one-period model, but accounts for early evidence of the interaction emerging in period 1, and full accumulated evidence emerging in period 2. Before period 1 two adversarial actors interact controversially. Incomplete early evidence emerges. Two media organizations are the players. Each player supports one of the actors ideologically, and exerts manipulation efforts including spin control to persuade media consumers that the actor he represents is righteous and should not be blamed. Media manipulation effort is interpreted broadly to include competition, verbal fighting, etc. Hirshleifer [
7] interprets fighting as a metaphor, i.e., “falling also into the category of interference struggles are political campaigns, rent-seeking maneuvers for licenses and monopoly privileges [
8], commercial efforts to raise rivals’ costs [
9], strikes and lockouts, and litigation—all being conflictual activities that need not involve actual violence.” The early and full evidence, and a variety of characteristics of the two players are incorporated into the game they play.
Hardly any literature exists on the phenomenon. Allcott and Gentzkow [
10] analyze fake news and social media in the 2016 US election. Blom and Hansen [
11], Zannettou, Chatzis, Papadamou, and Sirivianos [
12], and Khoja [
13] consider clickbait news. Kshetri and Voas [
14] examine fake news within an economic perspective.
3. Analyzing the Model
Since the players make no strategic choices in period 2, the game is technically a one-period game with strategic choice variables
and
in period 1. Differentiating player
’s expected utility in (5) with respect to his free choice variable
in period 1, and equating with zero, gives:
Solving (6) when Assumption 1 is satisfied gives:
The second order derivatives, inserting (7), are satisfied as negative, i.e.,
Inserting (7) into (5), when Assumption 1 is satisfied, gives the player’s expected utilities:
which are positive when,
which is a lenient restriction on the contest intensity
. For equivalent players (10) simplifies to
. When (10) is not satisfied, assume without loss of generality that
, which means that player 2 is disadvantaged e.g., due to a higher unit effort cost
. To avoid negative expected utility, player 2 exerts zero effort
earning zero expected utility
. If player 2 chooses zero effort
, player 1 cannot choose arbitrarily low but positive effort,
, which would not be an equilibrium, since player 2 would deviate by choosing some positive effort. Hence, we assume that player 1 chooses an effort
which deters player 2 from receiving positive expected utility
. This is accomplished by solving player 1’s first order condition
, i.e., the first Equation in (6), together with
determined by (5). These are two equations with two unknown
and
which are solved to yield,
which cannot be solved analytically, but is illustrated numerically in the next section.
Property 1. For the interior solution when Assumption 1 is satisfied,
,
,
,
when
,
,
. Proof.
Appendix B Equations (A1), (A2), (A3), (A4).
Intuitively, a higher unit effort cost in period 1 discourages player causing lower effort and lower expected utility . In contrast, higher causes higher expected utility for player , and lower effort when the specified inequality is satisfied. The specified inequality is more easily satisfied when , and are high, which advantage player .
Property 2. For the interior solution when Assumption 1 is satisfied,
,
,
,
when
,
,
. Proof.
Appendix B Equations (A5), (A6), (A7), (A8).
Higher stake in the interaction in period 1 for player induces higher effort and higher expected utility . In contrast, higher causes lower expected utility for player , and higher effort when the same inequality as in Property 1 is satisfied.
Property 3. For the interior solution when Assumption 1 is satisfied,
,
,
when
,
when
and
,
when
,
when
. Proof.
Appendix B Equations (A9), (A10), (A11), (A12).
The impact of player ’s proportionality parameter depends on whether the early evidence supporting player in period 1 is lower or higher than the accumulated evidence supporting player in period 2. When , so that player benefits from transitioning from period 1 to period 2, higher induces player to exert higher effort and he receives higher expected utility . In contrast, player receives lower expected utility , and exerts higher effort when the same inequality as in Properties 1 and 2 is satisfied.
Property 4. For the interior solution when Assumption 1 is satisfied,
,
,
when
,
when
and
,
when
,
when
. Proof.
Appendix B Equations (A13), (A14), (A15), (A16).
The impact of player ’s time discount parameter is equivalent to the impact of the proportionality parameter except that is confined to the interval , while is unbounded from above, i.e., .
Property 5. For the interior solution when Assumption 1 is satisfied,
,
,
when
,
when
and
,
when
,
when
. Proof.
Appendix B Equations (A17), (A18), (A19), (A20).
Property 5 assumes the intermediate value for the early evidence ratio intensity in period 1, to simplify the analysis. More early evidence supporting player in period 1 causes higher expected utility for player and lower expected utility for player when , i.e., when player ’s unit effort cost is high compared with his discount parameter , proportionality parameter , and the accumulated evidence supporting him in period 2. More early evidence supporting player in period 1 causes higher effort for player when the same inequality as in Properties 1,2,3,4 is satisfied. Higher also causes higher effort for player when player is disadvantaged with , and the same inequality as in Properties 1,2,3,4 is satisfied.
Property 6. For the interior solution when Assumption 1 is satisfied,
,
,
,
when
,
,
. Proof.
Appendix B Equations (A21), (A22), (A23), (A24).
Property 6 also assumes the intermediate value for the early evidence ratio intensity in period 1, to simplify the analysis. Again, and intuitively, more accumulated evidence supporting player in period 2 causes higher effort expected utility for player and lower expected utility for player . Higher causes higher effort for player when same inequality as in Properties 1,2,3,4,5 is satisfied.
Property 7. For the interior solution when Assumption 1 is satisfied,
,
and
when
,
when
,
when
. Proof.
Appendix B Equations (A25), (A26), (A27), (A28).
Property 8. For the interior solution when Assumption 1 is satisfied,
,
,
and
when
and
,
and
when
. Proof.
Appendix B Equations (A29), (A30), (A31), (A32).
4. Illustrating the Solution
Referring to the scenario in the introduction, in this section we can think of actor 1 as Catholic Kentucky high school student, Nicholas Sandmann, and actor 2 as native American, Nathan Phillips. We can think of player 1 as the parts of the media that supported or identified ideologically with Nicholas Sandmann. Possible examples are the Covington Catholic High School newspaper and local media institutions in Covington, Kentucky, or various catholic media outlets. We can think of player 2 as the parts of the media that supported or identified ideologically with Nathan Phillips. Possible examples are native American media outlets, and the media institutions that Sandmann filed lawsuits against.
Figure 2 illustrates the solution with the benchmark parameter values
,
,
, which imply
,
,
. That is, actor 1 supported by player 1 is assigned substantial fault expressed as low
in period 1, and much less fault expressed as low
in period 2, and vice versa for actor 2 supported by player 2. That causes low actual unit effort cost
for player 1, and high actual unit effort cost
for player 2, at the benchmark. Player 2 nevertheless receives the highest expected utility
at the benchmark since the early evidence ratio
favors player 2 in the benchmark contest. In each of the eight panels one parameter value varies, while the other parameter values are kept at their benchmarks.
In
Figure 2 panel a, a high unit effort cost
for player 1 causes low effort
and low expected utility
for player 1,
, and high expected utility
for player 2. Player 2 is advantaged when
is high, which does not induce a need to exert high effort
, and
. As
decreases, the players have equal unit effort costs when
. Then, player 1 exerts high effort
and receives low expected utility
, and vice versa, player 2 exerts low effort
and receives higher expected utility
. Although, player 1 is rewarded with a low actual unit effort cost
at the benchmark, the contest is not sufficiently beneficial for player 1. That is, player 2 is advantaged at the benchmark. As
decreases below 1 to
, the players receive equal expected utilities
. Decreasing
further to
causes player 1’s actual unit effort cost to be
, enabling player 1 to exert arbitrarily high effort
at no cost. Hence for
, player 1 receives expected utility
, and player 2 exerts effort
and receives expected utility
.
In
Figure 2 panel b, increasing stake
in the interaction in period 1 for player 1 causes increasing effort
and increasing expected utility
for player 1. From (7),
, see
Appendix C Figure A1. From (9),
In contrast, player 2’s effort
is inverse U shaped as
increases. This common phenomenon arises because player 2 is advantaged when
is low, receiving high expected utility
, and disadvantaged when
is high, receiving low expected utility
. Inserting into (7) and (9),
If
, rather than
varies along the horizontal axis in panel b,
, where player 2 is advantaged throughout since player 2 is advantaged at the benchmark
.
In
Figure 2 panel c, decreasing the proportionality parameter
which scales the strength of the reward
for player 1 has an impact similar to increasing player 1’s unit effort cost
in
Figure 2 panel a, due to the opposite roles
and
play in player 1’s actual unit effort cost
when
is negative. Hence when
is low,
,
, and
are low, and player 2’s expected utility
is high. As the proportionality parameter
increases, player 1 benefits from the lower actual unit effort cost which causes higher effort
and higher expected utility
for player 1, and lower expected utility
for player 2. As in
Figure 2 panels a and b, player 2’s effort
is inverse U shaped due to being advantaged when
is low and disadvantaged when
is high. When
increases to
, player 1’s actual unit effort cost decreases to
, enabling player 1 to exert arbitrarily high effort
at no cost. Hence for
, player 1 receives expected utility
, and player 2 exerts effort
and receives expected utility
.
In
Figure 2 panel d, varying player 1’s time discount parameter
between 0 and 1 when
is equivalent to varying player 1’s proportionality parameter
between 0 and 1 when
, since
and
only occur as
.
Figure 2 panel d highlights how disadvantaged player 1 becomes by being shortsighted expressed with low
. That is, player 1 does not envision the reward flowing from
being negative, exerts low effort
and receives low expected utility
. In contrast, player 2, endowed with the benchmark discount parameter
, benefits from player 1’s shortsightedness when
is low, and receives high expected utility
.
In
Figure 2 panel e, decreasing player 1’s early evidence
supporting player 1 in period 1 below the already low benchmark
increases his reward
, but decreases the evidence ratio
in (1) and (5). Player 1 gets less incentive to conduct media manipulation effort since
is low, but can manipulate the media more cheaply since his actual unit effort cost
is low. Hence decreasing
below
causes player 1’s effort
to be inverse U-shaped and eventually decrease towards zero, while his expected utility
decreases to zero, and player 2’s expected utility increases to
when
. In contrast, increasing player 1’s early evidence
above his benchmark
decreases his reward
, causing his actual unit effort cost
to increase. When
, the reward becomes a punishment, since the early evidence
supporting player 1 in period 1 is higher than the accumulated evidence
supporting player 1 in period 2. That gives a higher actual unit effort cost causing player 1’s effort
to decrease. As
increases, player 2’s effort
is slightly inverse U shaped, player 1’s expected utility
increases, and player 2’s expected utility
decreases.
In
Figure 2 panel f, increasing player 1’s accumulated evidence
supporting player 1 in period 2 above the already high benchmark
, increases his reward
, which decreases his actual unit effort cost
. Hence his effort
increases, reaching
when
(outside what is plotted in panel f), and his expected utility
increases. As
increases, player 2’s effort
is slightly inverse U shaped, and his expected utility
decreases. In contrast, decreasing player 1’s accumulated evidence
below his benchmark
decreases his reward
, causing his actual unit effort cost
to increase. Hence, his effort
and expected utility
decrease, while player 2’s effort
decreases and his expected utility
increases. As
decreases below
, player 1’s actual unit effort cost increases above his unit effort cost
since
becomes a punishment.
In
Figure 2 panel g, decreasing the contest intensity
below the benchmark
causes player 1 to exert lower effort
and receive lower expected utility
. A lower
causes efforts
and
to have lower impact on the contest, which becomes more egalitarian, and 100% egalitarian with no impact on the contest when
. Hence, player 1’s advantage of a lower actual unit effort cost
than
for player 2 at the benchmark gradually gets eroded. Hence, lower
causes higher expected utility
for player 2, sustained by decreasing effort
. In contrast, increasing
above the benchmark
causes higher effort
and expected utility
for player 1, and higher effort
and lower expected utility
for player 2, up to when
. Higher contest intensity
is usually characterized by both players exerting higher efforts, which is costly. The efforts
and
cannot increase without bounds. At some point the weakest player reaches his limit. Thus player 2’s expected utility is
when
. Player 2 may exert zero effort or some positive effort
when
, as long as his expected utility
is not negative. As discussed in the previous section, if player 2 chooses zero effort
, player 1 cannot choose an arbitrarily low, but positive effort
, which would not be an equilibrium, since player 2 would deviate by choosing some positive effort. Applying (11),
Figure 2 panel g for
is determined numerically. Continuous efforts
and
are ensured through
. As
increases above
, decreasing effort
by player 1 suffices to deter player 2 from exerting effort
to obtain positive expected utility
. Thus player 1’s expected utility
increases concavely,
, while
.
In
Figure 2 panel h, increasing the early evidence ratio intensity
from zero is beneficial for player 2,
, and not beneficial for player 1,
, accompanied by
. To see this, inserting the benchmark parameter values when
varies into (7) and (9) gives,
where the inverse early evidence ratio
raised to
, i.e.,
, favors player 2 in terms of higher expected utility
at the benchmark when
. Player 2 is favored increasingly when
, and decreasingly when
. Both players’ efforts
and
are inverse U shaped in
since one player is advantaged when the other is disadvantaged, and vice versa, with the highest media manipulation efforts
and
for intermediate
. In other words, for low early evidence ratio intensity, the fact that player 1 is subject to low early evidence is ameliorated, his effort matters less, and he receives high expected utility. In contrast, high early evidence ratio intensity amplifies how player 1 is subject to low early evidence, giving his lower expected utility.
5. Conclusions
A model is developed for two adversarial actors, which interact controversially. Early incomplete evidence emerges about which actor is at fault. A game is analyzed between two media organizations, as the players identifying ideologically with each of the two actors. Each player exerts manipulation efforts to support the actor he represents in a contest with the other player. We consider the two actors by comparison with the scenario in the introduction and simulation section, as high school student Nicholas Sandmann and native American Nathan Phillips, who interacted controversially January 18, 2019 at the Lincoln Memorial in Washington D.C., USA. We can think of the two players as two media organizations, which try to report the facts from the interaction, but additionally have ideological or other preferences that induce them to report favorably on the actor they identify with and support.
The game is technically a one-period game, where each player exerts one effort, but accounts for early evidence emerging in period 1 and full evidence emerging in period 2. If the full evidence equals the early evidence, each player’s unit effort cost has a fixed value. If the full evidence supports an actor more (less) than the early evidence, the player identifying with that actor is rewarded (punished) with a lower (higher) unit effort cost proportional to the strength of the additional (decreased) support and proportional to a time discount parameter. The article illustrates each player’s strategic challenge in determining the amount of media manipulation effort to exert, while accounting for the difference between the early and full evidence, the unit cost, and various other parameters.
To specify the model’s implications, properties are developed for the model’s eight parameters, which are illustrated with simulations relative to a benchmark. Without the loss of generality, actor 1 is supported by player 1 and is assumed to be substantially at fault, based on the early evidence, and much less at fault based on the full evidence. The impacts of player 1’s unit effort cost and stake in the interaction are discussed. Higher proportionality parameter, scaling the strength of the reward to player 1 for being disadvantaged with low early evidence, and higher time discount parameter for player 1, cause higher effort and expected utility for player 1, and inverse U shaped effort and lower expected utility for player 2. Inverse U shapes are common when one player decreases his effort when either, advantaged or disadvantaged, and exerts high effort when being neither, advantaged nor disadvantaged. Increasing the early evidence supporting player 1 from zero causes inverse U shaped efforts for both players, increasing expected utility for player 1, and decreasing expected utility for player 2. Increasing the full evidence supporting player 1 from zero causes increasing effort and expected utility for player 1, and decreasing expected utility for player 2. Increasing the contest intensity with the given benchmark is shown to increase both players’ efforts until a point where the disadvantaged player is deterred and receives zero expected utility. One implication for scenarios, such as the one between Nicholas Sandmann and Nathan Phillips, which gained widespread coverage and some degree of intensity, is that media organizations supporting one of the actors may potentially deter, outcompete, or silence the opposing media organizations. Finally, by increasing early evidence ratio intensity with the given benchmark demonstrates a common example where both players’ efforts are inverse U shaped, player 1’s expected utility decreases, and player 2’s expected utility increases. The prevalence of inverse U shaped results illustrates how the interaction between media organizations as players may often be characterized by one player or the other being advantaged, which may compromise, objectively, the neutral and ideology-free reporting.
The article provides a tool for media organizations, analysts, consumers, regulators, researchers, and regular people to better understand how adversarial interaction may play out in today’s continuously evolving media landscape. Realizing the interests of each player and actor, how each player and actor interact, and how new information becomes available over time, as illustrated in this article, may potentially enable everyone involved to contribute to mutually beneficial future media development. Future research should apply the model to more than two adversarial actors, more than two media players, more than two time periods, different kinds of information, and incorporate the role of media owners, regulators, advertisers, and consumers.