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A Research Paper on the Effect of Trivialization of the Attitude Object on the Polarization of the Attitude

Huub Schaft (10559418) University of Amsterdam

Date: June 2nd 2017

Bachelor thesis Social Psychology Instructor: Jonas Dalege

Course: Bachelor thesis Tweede versie

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Abstract

In this paper, the influence of trivialization on attitude polarization was researched. This was done through a survey with a manipulating text. 100 participants joined this study and were divided in two conditions in which they read a trivializing text on either border control or climate change. These texts were trivialized using data that made the attitude object seem unimportant. After reading this the participants would fill in a questionnaire with

questions on the importance and the attitude of 10 different subjects. From the results, it became clear that both the interaction effects of both the manipulation and the main analysis was not significant. However, after some simple main effects tests some results were found. The first was that the manipulation was only successful for the group who had read on climate control and this was only a very small effect. The second was that only the extremity of the attitude of the group that had read the text on border control had changed and that this extremity had increased which was not expected. Thus, it was hypothesized that this was due to the counteracting effects of trivialization and priming. Finally, this study stated that future research should continue looking into the influence of trivialization on attitude polarization but that it should focus on isolating trivialization from other influences such as priming.

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Since the election of the right-wing populist Donald Trump as the president of the United States of America this past November, the world has been wondering what caused these extreme opinions otherwise known as attitude polarization. Many different explanations have been thought of but none could clearly explain what might have caused it. An article of Fishwick (2016, 9 November) for example explained that this unexpected result arose because people did not want Hillary Clinton to win. Yet McKernan (2016, 9 November) explained this result by stating that it was caused by the shifting employment rate and that people truly believed that Donald Trump could make the land more prosperous. In the current study the focus will be on trying to scientifically explain the polarization of the opinions.

In previous research, a few other explanations than the ones mentioned above have been found for attitude polarization. For example, Boleslavsky, and Cotton (2015) state that extremism in elections is influenced by the amount of information that both parties produce about the quality and the characteristics of the candidate. They claim that more information about a candidate allows the voters to have a more complete image on the candidate, thus allowing them to form a stronger opinion on them. This in turn leads to more extreme opinions towards all the candidates. Thus, in the case of Donald Trump this led to a stronger favourable but also to a stronger unfavourable opinion towards Donald Trump

All these different explanations make it clear that extreme opinions are not a simple subject. One general conclusion however is that most of the topics on extreme opinions can be explained by attitude formation and-attitude polarization. There are many different theories that explain how attitudes are formed but the general conclusion is that when a person interacts with a certain object he/she forms an opinion about that object (Harton, & Latane, 1997; Tesser, & Leone, 1977; van der Maas, Kolstein, & van der Pligt, 2003). This opinion can then be seen as the attitude. The attitude can vary in valence, going from negative to neutral to positive (Krosnick, Boninger, Chuang, Berent, & Carnot, 1993). The attitude can also differ on extremity, involvement, certainty, and intensity (Krosnick, et al., 1993).

In this paper, the theory on how attitudes are formed by Dalege, Borsboom, van Harreveld, van den Berg, Conner, & van der Maas (2015) will be used. However, since this theory is quite abstract it will be explained using an example about the polarized attitude on Donald Trump. The paper of Dalege et al. (2015) states that attitudes exist of a network of all evaluative reactions toward an object and the interaction between these reactions. The

evaluative reaction or ‘nodes’ are beliefs, felt emotions and behaviours towards an object. In the case of Donald Trump the strong opinions towards him came forth from a lot of different interactions with him. Each interaction produces a collection of beliefs, felt emotions and

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behaviours and for every one of these beliefs, felt emotions or behaviours a node that is associated with Donald Trump is born. All these nodes associated with Donald Trump combined then form the attitude network a person has on Donald Trump. And each of these nodes can have a positive or a negative value. However, all the nodes do have an influence on each other which can mean that another node can influence a certain node to become negative as well. For example, if someone dislikes what Donald Trump says then a negative node is created. And because this person dislikes what Trump says, he might also think that his hair looks weird which causes the nodes to influence each other. All the values of the nodes in one network combined then decide whether the attitude is positive or negative.

If a person is very attached to an object and believes that the object is personally important then the connections between the nodes and the object become stronger, which means that-a node has a stronger influence on the other nodes it has a connection with. According to this, if one node is positive the other nodes it has a strong connection with are also more likely to be positive. This results in a stronger attitude toward the object. With Donald Trump this would mean that someone who thinks Donald Trump is very important has a stronger attitude than someone who does not think that Donald Trump is important.

Depending on the strength of the connections an attitude network can reside in a different amount of network states. As mentioned before, ratio of the positive versus negative values of all the nodes decide-whether the attitude is positive or negative. However, the value of a node can switch between positive and negative. Thus, if a network has a lot of nodes many different ratios of positive and negative are possible. And each of these combinations of positive and negative nodes form a state the network can reside in. For example, if a person thinks negatively of Donald Trump because he believes Donald says stupid things then he has more negative than positive nodes in his attitude network of Donald Trump. However, if Donald Trump were to suddenly say a lot of things that sound right to this person then it is possible that the value of a node of this person would change. This can mean that the attitude becomes less negative since there are-fewer negative nodes and more positive nodes or it can mean that the attitude switches from negative to positive if the number of positive nodes starts to outweigh the negative nodes. And this is possible for all beliefs, felt emotions or

behaviours that have created nodes, thus allowing the network to reside in many different states. However, when the connections between the nodes and the object are strong the nodes start to influence each other more which results in a network where the nodes are often all negative or all positive. This would be a polarized attitude.

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Based on the information provided above it can be assumed that to change an attitude, three factors should be considered. These are the number of nodes a person has in that

attitude’s network, the ratio of positive versus negative notes there are in that attitude’s network. And the strength of the connections in the network caused by the importance the person attaches to this attitude. So, one way to change a strong attitude is if the attitude receives so much contradicting input that the value of the contradicting nodes outweighs the value of the original nodes. However, the amount of contradicting input depends on the number of nodes a person has in his network and the strength that the connections in this network have.

To explain this with the case of the Donald Trump example, imagine two situations where there is a party that tries to convince someone that Donald Trump is a bad president. In the first situation, the person has a small, weak and barely positive attitude network about Donald Trump. Because the network is small and weak, there are only a few nodes which barely influence each other. Furthermore, since the attitude network is barely positive the amount of negative and positive nodes barely differs. Thus only a few negative nodes that oppose the current attitude might change the structure and the value of the attitude network.

However, if this person had a big, strong and extremely positive attitude network about Donald Trump then it would mean that there are a lot of nodes which have a strong influence on each other and that the positive nodes severely outweigh the negative nodes. In this case, a lot of negative nodes that oppose the current attitude are needed to change the structure and the value of the attitude network, but it still might change.

Multiple theories also explain this, such as the catastrophe model of van der Maas, Kolstein, & van der Pligt, (2003) and the causal attitude network model of Dalege et al. (2015). For example, according to the catastrophe model there are two variables that influence the change of an attitude. The first is information which can change an attitude from positive to negative. The second is involvement, which change the rigidness of the attitude. This means that an attitude is resistant to a certain amount of contradicting input depending on the involvement of the person in the attitude. In both situations, if enough contradicting input is presented the network will completely switch to the other state thus changing the valence of the attitude. However, with low involvement this change is very fluid whereas with high involvement the change is very rigid and only performs sudden jumps. This means that with high involvement the attitude can only switch between extremely positive and extremely negative.

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And a similar article on the catastrophe theory of attitudes by Latané and Nowak (1994, as mentioned in Harton, & Latane, 1997) gives the same explanation for the rigid change of polarized attitudes. Furthermore, the theory of attitude change through opposing information is also supported by many different papers on the effect of information on attitudes (Chaiken, & Yates, 1985; Vinokur, & Burnstein, 1978; Tesser & Leone, 1977).

However, in the case of an extremely polarized attitude, change through opposing information is not very effective or efficient. Thus, it might be better to focus on changing another factor. Another viable way of changing polarization might thus be through changing the strength of the connections between nodes. As described above by the causal attitude network theory of Dalege et al. (2015) the-strength of the connection between two nodes decides how much these nodes influence each other and how this can lead to polarized attitudes. And according to this theory the strength is based on the importance a person attaches to the attitude object. And evidence for this can also be found in other empirical articles.

For example, in an empirical-article, it was shown that higher involvement in an object led to a stronger attitude about that object (Krosnick et al., 1993). This shows that high

involvement and polarization might be related. A different paper on involvement also shows that more involvement leads to stronger attitudes and thus to polarization (Ann Smith, 1989). Furthermore, also the catastrophe model offered shows that higher involvement lead to a more extreme attitude and more polarization (van der Maas, Kolstein, & van der Pligt, 2003; Latané & Nowak, 1994, as mentioned in Harton, & Latane, 1997). Thus, it is safe to assume that there is a relationship between attitude polarization and involvement.

However, the previous literature did not look at the possibility of lowering polarization through lowering the involvement. Since it was proven that higher involvement is due to a higher believe of importance in an object and higher involvement leads to stronger connection between nodes, it is possible that lowering this involvement might decrease the strength of the connections. This might make it easier for nodes in a network to switch between values since the other nodes less influence-it. And-if the values of nodes change the attitude should

become less polarized. Therefore, it might be possible to change the polarization of an attitude by changing the importance a person attaches to an attitude object through trivialization.

As mentioned before most of the previous research only looks at whether more involvement leads to more polarization-but none look at lowering involvement, even though there is some evidence suggesting that there might be effect there. Therefore, it might be beneficial on a scientific front to also study the influence that less involvement might have on

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attitude polarization. This might bring more clarity about the way that attitude polarization works. Besides the scientific benefit this might have it can also have a productive value for society. Currently the world is plagued by people who perform extreme acts, such as terrorist from Isis, based on their extremely polarized believed. If a way to reduce polarization can be found this might decrease the amount of people who perform such acts.

Since there is evidence suggesting a positive connection between involvement and attitude polarization, it might be possible to decrease the polarization of the attitude by decreasing the importance a person attaches to the object. That’s why this paper will mainly focus on reducing polarization. This will-be done by manipulating the importance of an attitude in an experiment with data showing the insignificance of the contribution of the Netherlands for either climate change and refugee management. The polarization will then be checked through a questionnaire of which the results will be analysed and interpreted. With this study, we will try to answer the question: What is the influence of trivialization of the attitude object on the polarization of the attitude? Since previous research on how attitudes are formed and how involvement affects this formation concluded that there is a positive

relationship between polarization and involvement it is hypothesised that lowering the involvement will decrease the polarization of the attitude.

Method

Participants

In this study 106 people participated of which six were not able to finish the survey before the closing date. These six participants were excluded-from the data set and were not used in the analysis. Of the remaining participants 69 were female and 31 were male. The mean age of the sample was 21 years old with a standard deviation of 2.15, and most of the participants were first year psychology students (59%). The participants were randomly divided over the two conditions with 51 participants in the climate control condition and 49 participants in the border control condition.

Pilot study

A pilot study was used to test on which topics the participants had an extreme opinion. This study consisted of 8 different subject such as border control, climate change, the student loan system, and meat tax. The study was done by 16 participants and it was estimated from

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the results that the participants had the most extreme opinion on the subjects climate change and border control.

Measures

For this study, a questionnaire with 10 attitude objects with each 6 questions was used. The questions were divided in 3 questions on the personal importance per subject and 3 questions on their attitudes per subject. The subjects-consisted of border control, climate change, and eight other random subjects that were the same for both conditions. These questions were scored with a slider with values between 0 and 100. Two of the subjects, border control and climate change, were used as the measurement and were based on a pilot study to test the extremity of the attitude towards the subject. The other eight subjects were randomly chosen to mask the intentions of the questionnaire. The questions were based on questions used in earlier research on attitudes. Examples of such questions are ‘When I have to vote on an increase of government funding for the reduction of climate change, I am’ with a slider ranging from for or against and ‘I care about the subject ’border control for refugees.’’ with a slider ranging from disagree to agree. The reliability of these questions was tested with a Cronbach alpha test. This showed-that the reliability of the attitude questions on border control and climate control and the importance questions on climate control were all above .9 which is very good. The reliability of the importance questions on border control was above .7 which is also good. This means that it can be assumed that the questions within one of the groups measured the same construct.

Furthermore, four different texts were used. One text contained trivializing

information about climate change and another text contained trivializing information about border control. The trivialization was done by making it seem that the actions of the

Netherlands were not that important on global scale. This should decrease the involvement of a participant with the topic of the text. For this purpose, the texts were mostly filled with statistics acquired from the CBS. The other two texts contained explanatory information from the Dutch government website on either student financing or financing for art and culture. These texts were added to distract the reader from the actual goal of the study so that the participants would not answer the questions dishonestly.

Procedure

Subjects could pick our experiment from a list of possible experiments on the site of the laboratory of the university of Amsterdam. The rewards for participation were study

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credits that they are required to get for passing a course. After picking our experiment they were send to the site with the survey. Here they were randomly assigned to two different conditions, the climate change condition or the border control condition. In the climate change condition, they were asked to first read two short texts on two random subjects and then one short trivializing text on climate change. In-the border control condition, they were asked to first read two short texts on two random subjects and then one short trivializing text on border control. After this the participants from both conditions were asked to fill in the

questionnaires. Next the participants were asked to fill in some personal data such as their gender and their age.

When they were finished with these questions they were debriefed about the manipulation and thanked for their participation. Then they would receive their credits.

Data analysis plan:

First, the reliability of the survey will be tested. This will be done by calculating a Cronbach Alpha for the two different questions groups on importance and the two different question groups on attitude. Second, the assumptions of the manipulation check will be tested. Third, the manipulation check will be done. This-will be done by analysing the mean scores on the importance questions with the condition and the question group. This will be done by using a mixed design ANOVA. The dependent variable will be the mean importance scores and the independent variables will be the-condition and the question group. Condition-will be

manipulated between subjects and the question group will be measured within subjects. After this a simple main effects analysis-will be performed to see if there was an effect for either of the manipulations. The results of these tests will be analysed and will confirm whether the manipulation succeeded or not. Fourth, the assumptions of the main analysis will be checked. Fifth, the main analysis will be performed. This-will be done by using another mixed design ANOVA. The dependent variable will be the mean attitude extremity scores and the

independent variables will be the condition and the question group. Condition will be

manipulated between subjects and the question group will be measured within subjects. After this a simple main effects test will be performed to-see if either of the manipulations had any results. The results of these tests will be analysed and will confirm whether trivialization has an influence on attitude-polarization or not.

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Results

Before the analysis was performed the data on the attitude questions was rescored to create an extremity statistic. This was done-by subtracting the middle value of 50 from each of the scores. After this the questions about the extremity of the attitude on climate control were grouped in one group. The extremity scores of the attitude on border control were grouped in a different group. The same was done for the questions on the importance of climate control and border control resulting in four distinct groups.

Next the normality of the manipulation-check was tested through a histogram. This showed that there was no normal distribution in the importance of either of the conditions but that they were extremely skewed to the right. However, since the multiple repeated measures ANOVA is fairly robust the skewness was not a problem. Second the Levene’s test of equal variances was done, which showed that there were unequal variances for the scores on the questions on climate control, F (1,98) = 10.27, p = 0.002. However, this is also not a problem since the repeated measures analysis is robust enough to ignore these results. Furthermore, the results of the Levene’s test for the questions on border control were not significant, F (1,98) = 0.85, p = 0.358, which is good.

Then the manipulation check was performed by using a multiple repeated measures ANOVA. From this analysis, no significant results were found. There was no main effect found for either the question group, F (1,98) = 0.28, p = .594, η2 = .003, or for the condition, F (1,98) = 2.413, p = .124, η2 = .024. This means that there was no difference in score of

importance between the conditions or between the question groups. There was also no interaction effect found between the-condition and the importance, F (1,98) = 1.55, p = .215, η2

= .016. This means that the importance scores per question group were not different depending on the topic. However, it might be possible that one of the two objects has been successfully manipulated.

Thus, a simple main effects test was performed. From this test, it was found that participants that had read the text on border control scored the importance of the subject on border control slightly higher than the participants who had not read this text. This can be seen in figure 1. The change in the score on importance of the border control question group was not significant between the two conditions, F (1,98) = .37, p = .542, η2 = .004. This means that the manipulation of border control has failed. This was not in line with the expectations. From the results, it can be interpreted that the manipulating text about border control might even have had a reverse effect on the importance of the subject to the

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participants. This can also be seen in figure 1. However, since the result was insignificant this cannot be statistically proven.

From the simple main effects test it was also found that participants that had read the text on climate control scored the importance of the subject on border control slightly lower than the participants who had not read this text. The change in the score on importance of the climate control question group was not significant between the two conditions, F (1,98) = 3.32, p = .071, η2

= .033. This means that the manipulation of climate control has also failed. This can also be seen in figure 1. However, since there is a trend, it might still be interesting to do the analysis of the attitude change between the conditions.

Figure 1. Mean Importance Scores per Condition per Question Group

Before this test was done, the assumptions-were checked. Here the data was also not normally distributed but was also skewed to the right in both conditions. However, this was expected since this study only looks at-polarized opinions. And since the multiple repeated measures ANOVA is fairly robust the skewness was not a problem. The Levene’s test for the questions on the attitude towards climate control was not significant, F (1,98) = 2.20, p =

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.141. The Levene’s test for the questions on the attitude towards border control was also not significant, F (1,98) = 2.25, p = .136. This means that the assumption of equal variances was not violated. After checking the assumptions, the main analysis of the change in scores on the attitude questions were compared between conditions. The results of this analysis showed that there were no significant main effects for the condition, F (1,98) = 3.531, p = .063, η2 = .035, or for the question group, F (1,98) = 3.469, p = .066, η2 = .034. This means that there was no difference in score of attitude extremity between the conditions or between the question groups. The results also showed that there was no significant interaction effect between the condition and the attitude scores, F (1,98) = .535, p = .466, η2 = .005. This means that the attitude extremity scores per question group were not different depending on the topic. A simple main effects analysis was performed to see whether one of the two conditions might have been significant.

The results of the simple main effects analysis showed that the participants that had read the text on climate control had a slightly lower attitude score on the topic of climate control than the participants who-had not read this text. This can be seen in figure 2. The difference in scores was not significant, F (1,98) = 1.38, p = .243, η2 = .014, which means that the manipulation used in this test had no effect on the attitude scores of the participants. This was not in line with the expectations.

The results of the simple main-effects analysis also showed that the participants that had read the text on border control had a slightly higher attitude score on the topic of border control than participants who had not read this text. This is shown in figure 2. The change in scores was almost significant, F (1,98) = 3.68, p = .058, η2 = .036, suggesting that there might be an effect here. However, the result was not in line with the expectations since the attitude scores increased after reading a text with trivializing data on border control.

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Figure 2. Attitude Extremity Score per Condition per Question Group

Discussion

In this paper, the influence of trivialization on the polarization of attitudes was studied. After performing a manipulation check to see if the manipulation had worked it was shown that there was minor difference in the importance of the subject between reading and not reading a trivializing text about a topic. This means-that the manipulation failed. An explanation for this might be that the participants did not consider the data to be trivializing. However, a simple main effects analysis showed that the text on climate control might have had a small

trivializing effect on the participants. Thus, it is possible that the text was not strong enough. The results of the main analysis showed that there were no significant interaction effects between the attitude extremity score and the trivializing effect of the text. This means that the null-hypothesis could not be rejected. Thus, there was no relationship between

trivialization and the polarization of attitudes found in this paper. This was not in line with the expectations of this study or with previous research.

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An explanation for why the text on border control did not have a trivializing influence and the text on climate control almost did have such an effect is because the subject of border control might be less abstract than the subject of climate control. From previous research, it is clear that less abstract objects are better to grasp for most people (Small, Loewenstein, & Slovic, 2007; Das, Kerkhof, & Kuiper, 2008). Thus, it is possible that people have a stronger and more accurate opinion on border control than on climate control. And a stronger and more accurate opinion is harder to trivialize since the trivializing information might be more easily discarded.

However, when a simple main effects analysis was performed, it was shown that there might have been an increase in the polarization of the attitude on border control after reading a trivializing text on this topic. These findings might be explained-by the fact that the

trivialization was not strong enough. In this-case-a stronger trivializing text might have had more of an effect. Another explanation might have been priming. Reading a text on a subject might cause the memories of earlier arguments on the topic to become active, which is called priming. (Lord, Ross, & Lepper, 1979; Munro & Ditto, 1997; Wojcieszak, 2011). These memories might increase the extremity of the attitude on the topic. Thus, people who read the text on border control as well as the people who read the text on climate control were primed. In this case priming can be seen as the opposite of trivialization since priming should increase the importance of the topic and trivialization should decrease the importance of the topic. However, since the trivialization failed for-those who read the text on border control they were only exposed to the priming effect of the text. Thus, it is possible that the change in the attitude of the people who read the text on climate control was balanced out by both priming and trivialization but the change in the attitude of people who read the text on border control was only influenced by the influence of priming thus increasing the extremity of their attitude on this topic.

Since none of the interaction effects were significant though, it is possible that these explanations are wrong as well. However-since there were two changes that were almost significant it is important that future research focusses on the two points mentioned above. It can do this by making the trivializing texts stronger and by testing beforehand whether these texts have the desired effect. Furthermore, in future research the priming and trivialization should be isolated by including a text that has no trivializing information but just neutral information on a certain topic and by comparing this group with a group that did read

trivializing information on this topic. The difference between these two groups should then be the influence of trivializing information.

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Concluding this study tried to answer the research question: What is the influence of trivialization of the attitude object on the polarization of the attitude? From the results it was shown that there was no influence between trivialization of an attitude object on the

polarization of the attitude. However, some simple main effects tests showed that there is a possible influence of trivialization on the polarization of an attitude but that this influence might be negated by other influences of information such as priming. Thus, there is plenty more to be researched on the connection between trivialization and attitude polarization.

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Bibliography

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Boleslavsky, R., & Cotton, C. (2015). Information and extremism in elections. American

Economic Journal: Microeconomics, 7(1), 165-207.

Chaiken, S., & Yates, S. (1985). Affective-cognitive consistency and thought-induced attitude polarization. Journal of Personality and Social Psychology, 49(6), 1470.

Dalege, J., Borsboom, D., van Harreveld, F., van den Berg, H., Conner, M., & van der Maas, H. L. J. (2015). Toward a formalized account of attitudes: The Causal Attitude

Network (CAN) model. Psychological Review, 123, 2-22.

Das, E., Kerkhof, P., & Kuiper, J. (2008). Improving the effectiveness of fundraising messages: The impact of charity goal attainment, message framing, and evidence on persuasion. Journal of Applied Communication Research, 36(2), 161-175.

Fishwick (2016, 9 November) https://www.theguardian.com/us-news/2016/nov/09/why-did-people-vote-for-donald-trump-us-voters-explain

Harton, H. C., & Latane, B. (1997). Information-and thought-induced polarization: The mediating role of involvement in making attitudes extreme. Journal of Social Behavior

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Krosnick, J. A., Boninger, D. S., Chuang, Y. C., Berent, M. K., & Carnot, C. G. (1993). Attitude strength: One construct or many related constructs? Journal of personality

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Lord, C. G., Ross, L., & Lepper, M. R. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of

personality and social psychology, 37(11), 2098.

Van der Maas, H. L. J., Kolstein, R., & van der Pligt, J. (2003). Sudden transitions in attitudes. Sociological Methods & Research, 32, 125–152.

McKernan (2016, 9 November) http://www.independent.co.uk/news/world/politics/president-donald-trump-why-people-voted-for-republican-wins-us-election-2016-a7407541.html Munro, G. D., & Ditto, P. H. (1997). Biased assimilation, attitude polarization, and affect in

reactions to stereotype-relevant scientific information. Personality and Social Psychology Bulletin, 23(6), 636-653.

Small, D. A., Loewenstein, G., & Slovic, P. (2007). Sympathy and callousness: The impact of deliberative thought on donations to identifiable and statistical victims. Organizational Behavior and Human Decision Processes, 102(2), 143-153.

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Tesser, A., & Leone, C. (1977). Cognitive schemas and thought as determinants of attitude change. Journal of Experimental Social Psychology, 13(4), 340-356.

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