The purpose of this paper is to examine whether news media moderates the impact emotions and thinking style have on the framing effect. We study this experimentally, to establish causal direction, by manipulating emotional stimuli and valence of a news story. The news story is our news media context, and concerns the Ukraine/Russia conflict, which is highly salient at the time of writing. Participants with high levels of analytical thinking experiencing negative emotions are hypothesized to be the least susceptible to framing effects. The uniqueness of our contribution is an emphasis on interaction effects and applying a multi-method design to examine a hitherto understudied scenario.
We are faced with a great paradox in our day and age. News media bombards us with a vast amount of information, notwithstanding our strong disposition to circumscribe our information processing abilities; i.e. cognitive mising (Stanovich, Toplak, & West, 2010). A consequence of this is that we are liable to base our decisions on caricatures of reality (Hammond, Keeney, & Raiffa, 2006), even relying on our gut feeling (emotions) to sway us in the right direction. One key cognitive trap in this regard is called the framing effect, which refers to our susceptibility to take the manner in which options are presented at face-value without further analysis (De Martino, Kumaran, Seymour, & Dolan, 2006). People have been shown to respond differently to different, but objectively equivalent, descriptions of the same problem (Ma, Feng, Xu, Bian, & Tang, 2012). Differences in thinking style has however been found, in that some people are more minded to be analytical, while others lean towards their intuition (Kahneman, 2012). People seem predisposed toward using automatic modes of processing when making decisions, even important ones (Sanfey & Chang, 2008). This is highly unfortunate and calls for research aimed at the discovery of how emotions, thinking style, and news media tricks decision makers, and how to avoid it. This yields the following research question: How does emotions and thinking style influence susceptibility to the framing effect in a news media context?
Theory and Research Design
Framing effect, news media, emotions, and thinking style were recurring keywords that popped-up in our initial literature review, but there was a great lack of research on their interrelation. News media is arguably the unrivaled modern-day framer of information (Kennis, 2013), which incited us to put forth the proposition that it is likely to moderate the strength of the relationship between our independent (emotions and thinking style) and dependent (framing effect) variable(s). There are however different kinds of mass media, like e.g. film and radio, which is why we limit our focus to news media outlets. News media is of more interest since it arguably has a deeper impact on people’s critical decision-making processes than say movie or the advertising industry (Herring & Robinson, 2003).
An experimental research design was found best suited for the study in question, since we want to clarify causal relationships, and since we want to build on the foundation of other researchers in this field, who mostly opt for an experimental design. The theoretical rationale behind our selection of variables, and how we contribute to the literature, will be presented in separate sections successively along with a presentation of some emerging theories on how emotions and thinking style are interrelated.
The Framing Effect
The human mind has evolved shortcut-strategies that deliver sufficient, but not always great, solutions to real world problems (Hardman, 2009). These heuristics are rules of thumb, unconscious routines, utilized to reduce complexity, time, and effort required to make good decisions (Kane & Webster, 2013; Plous, 1993). They can however lead to entrapping biases like the framing effect, which can spiral out of control without mind-guards (Hammond et al., 2006).
The term “framing effect” refers to the finding that subjects often respond differently to different descriptions of the same problem (Frisch, 1993), which demonstrates decision makers´ limited cognitive abilities; a central part of what Simon (1999) labeled “bounded rationality”. A classic example of the framing effect is Tversky and Kahneman´s (1981) Asian disease problem. In this experiment participants were presented with a scenario concerning an outbreak of an unusual Asian disease expected to kill 600 people. Two alternative programs to combat the disease were proposed to two different groups, where the programs in reality saved an equal amount of lives, but differed with regards to whether they talked of “lives saved” or “lives lost”. In Kahneman and Tversky’s (1981) experiment, a majority of participants became risk averse when given a possibility to save 200 lives for sure, rather than gambling on saving more lives; a classical pattern confirmed by Kühbergers meta-analysis (1998).
Piñon and Gambara (2005) have however cautioned that the framing effect is used quite informally in the scientific literature, and often used interchangeably with some vague definition of risky-choice framing. They build on the typology developed by Levin, Schneider and Gaeth (1998), in which risky-choice framing situates decision problems in terms of losses and gains by using negative or positive frames, but confusion nevertheless still prevails in the literature. We experienced this issue ourselves when reviewing the literature on the topics of our research paper, and had to strike a balance in order to utilize these papers for our research. Hence, the type of framing we study in this paper can most accurately be classified under the general heading of valence framing, since most of our sources employed conceptualizations of framing similar to risky-choice- and attribute framing. Valence-framing is a group of framing effects (risky-choice-, attribute- and goal-framing), in which the same critical information is phrased either in a positive frame, or in a negative frame (Levin et al., 1998). Our experimental context have aspects in common with both risky-choice- and attribute framing, since the news article stimulus is similar to attribute framing, while the risk of WW3 frame is characteristic of risky choice.
Experiments have demonstrated that subjects who become victims of the framing effect do not agree that the two versions of the problem are equivalent, even when directly comparing them (Frisch, 1993). Prospect theory has provided the main theoretical framework for explaining valence-based framing effects (Tversky & Kahneman, 1974 in Plous, 1993). In this theory, value is defined in terms of gains and losses, with an s-shaped curve depicting how value shifts depending on what kind of reference point one operates with; predicting that preferences will depend on how a problem is framed. Decision makers tend to be risk averse if the reference point is defined such that an outcome is viewed as a gain, but tend to be risk seeking if an outcome is viewed as a loss (Plous, 1993). Prospect theory’s biggest weakness is that it does not provide a thorough understanding of the cognitive processes that underlie framing effects (Hardman, 2009; Levin et al., 1998), which is why we investigate the explanatory power of two different cognitive mechanisms (independent variables), namely emotions and thinking style.
We suspect that the strength of our independent variables on the framing effect will be modified by our participants being situated in a news media context, since news outlets plays an important role in framing and setting the agenda in our information age (Entman, 2007). How these cognitive mechanisms impact the emergence of the framing effect is easier to study in current times, due to recent advances in neuropsychology.
News Media as Moderator
Our decision to use media as moderator was partly based on suggestions for future research in a review of the conceptual issues in framing theory by Borah (2011), and a curiosity about its seemingly expected impact on framing. He proposes that framing theory is a fractured research program in which more holistic approaches are desired, like the interaction effects we want to examine. Lament about this conceptual under-development was previously put forward by Entman (1993), who argued that there is no clear operationalized definition of this construct. It is hence of interest to see how a news story from a respected news outlet, an externally generated stimulus, moderates the effect of emotions and thinking style since they are generated internally. Due to its current salience, we handed out differently valenced news stories about the Ukraine/Russia conflict to our experimental group, the control group will be given a neutral political science article about the topic.
The power of news outlets is a hot topic, and a case can be made for the proposition that reality is filtered through the offices of media and news conglomerates (Herring & Robinson, 2003; Kennis, 2013). It is in these news offices that an angle is determined for the selected news items, such as whether the glass is half-full (good) or half-empty (bad) (Entman, 2007; Noorzai, 2013; Rivers, 1991). How individuals react to world events might hence be influenced by how it initially was framed in the media (Kepplinger, Geiss, & Siebert, 2012). This can result in valuable resources being spent on trivial issues, while more important news goes unmentioned. Experiments conducted by Kahneman (1981) actually showed that most people are more afraid of sharks than falling airplane parts, even though the latter kills a lot more than the former (Plous, 1993). This discrepancy might largely be due to how media frames sensation-seeking news, instead of presenting true facts. This overrated fear of sharks, might also suggest an interesting interaction between Hollywood and news media that goes beyond this paper. Such possible interaction effects between different kinds of mass media does however tantalizingly suggest that our findings might be generalizable to mass media more generally. It is nevertheless important to study how the framing effect is impacted by the role of news media, since clarification of this could make journalists and others more self-conscious of this effect; offering mind-guards.
Boydstun and Glazier (2013) studied media/news framing of the “War on Terror” in the light of Prospect theory and Self-identity theory, and they found that framing of the war shifted from a predominant use of “fear” (self-referential loss) frames to an increasing use of “charity” (other-referential gain) frames. Another interesting study was conducted by Dunham (2013), who compared news items from news outlets presumed to be conservative and liberal. He found that bias explained three quarters of the differences in framing between these outlets, which means that the angle on the same news items would differ substantially. This is likely to both impact the frames of the reader who consumes this information, but also the options a journalist has in these work environments. Based on these findings, fruitful research could be performed regarding current news stories and how powerful framing effects induced by the media really are.
Thinking Style: Kahneman’s Dual-processing model
The distinction between two different modes of processing information, one analytical and one intuitive, has a long history and goes by many labels (Epstein, 1994). Our focus will be on Kahneman’s (2012) dichotomy between System 1 and System 2 . Kahneman describes System 1 as operating automatically, with minimal effort and no sense of control. When this system runs into difficulty, it relies on System 2 to support it with more detailed and specific processing that may solve the problem the decision maker is dealing with. System 2 gives attention to effortful mental activities and monitors thoughts and actions suggested by System 1. This monitoring activity, which results in some thoughts being allowed and others not, is one of the main functions of System 2 (Kahneman, 2012).
Whether people use an analytical- (System 2) or intuitive (System 1) thinking style when faced with decision frames has a potentially large impact on subsequent judgment and decision making. Theories attempting to explain the framing effect, such as for example the “cognitive cost-benefit tradeoff theory”, states that the individual will refrain from committing to a complicated and time-consuming cognitive effort as long as possible (Payne, Bettman & Johnson, 1993 cited in Gonzalez, Dana, Koshino & Just, 2004). This implies a predisposition for intuitive thinking, which can be unfortunate because of its heavy reliance on heuristics, and therefore also potential framing effects (Morewedge & Kahneman, 2010). An alternative to this is the fuzzy-trace theory, which proposes that the framing effect is the result of superficial and simplified processing of information (Reyna & Brainerd, 1991). There are however individual differences in how people approach a task and process the information in question (Chatterjee, Heath, Milberg, & France, 2000; Hodgkinson & Clarke, 2007). This makes a strong point for why it is important to consider the propensity to use a certain thinking style when media frames are apparent. Additionally, knowledge about this is essential when trying to minimize framing effects.
To measure degree of analytical thinking, the need for cognition-scale was developed by Cacioppo and Petty (1982) and is frequently used in newer studies to detect propensity to engage in effortful thinking. Smith and Levin (1996) assessed the effect of framing on individuals using this scale. They found that people low on need for cognition were affected by framing effects, whereas individuals high on need for cognition were not. This finding is in line with Chatterjee et al (2000) and transferable to Kahneman´s theory, emphasizing that analytical thinking is more seldom associated with biases (Kahneman, 2012). Other researchers have also found that individuals who approach a decision problem with an analytic thinking style are especially insensitive to the influence of framing effects (McElroy & Seta, 2003). In line with this finding, the results of Simon, Fagley and Halleran (2004) showed that no framing effects were found among individuals high on need for cognition, who were in a deep processing condition.
Wong, Kwong, and Ng (2008) conducted a study showing results that contradicts with the abovementioned studies. They found that individuals scoring high on analytical thinking were more prone to escalation bias, and thus framing effects in decision situations, than low scorers. Wegener, Petty and Klein (1994) showed that this was also the case for subjects scoring high on need-for-cognition. As an extensions of both these studies, Igou and Bless (2007) underlines this point, and argue that framing effects were larger when conditions allowed for an analytic processing style. They also found that in some situations an analytical approach increased framing effects. Shiloh, Salton and Sharabi (2002) on the other hand highlighted that the combinations of high analytical and high intuitive thinking style, and low analytical and low intuitive thinking style were the ones most susceptible to framing effects. This finding contradicts the findings mentioned above, because in this study none of the thinking styles taken separately affected choices (Shiloh et al., 2002).
The research presented so far, shows that the answer to the question of which thinking style that is most affected by framing effects in every situation is by no means clear-cut. Even though the evidence seems more in favor of one of them, previous research has not to our knowledge extensively investigated the relation between framing effects and thinking style in a news media context. This is why our experiment will illuminate this relationship.
Catalytic for our decision to position emotions as one of our independent variables, was the interest this concept has received in the research community, and the opportunities for new developments (Angie, Connelly, Waples, & Kligyte, 2011; Gross & D’Ambrosio, 2004; Kepplinger et al., 2012). This interest is likely to be intensified by the conceptual strength of “emotions”, since clear neuropsychological markers for measurement has been found. Brain imaging techniques have been used to show how framing effects are particularly related to activities of emotion-related brain regions, suggesting a key role for the emotional system in mediating decision biases (De Martino et al., 2006; Kuo, Hsu, & Day, 2009; Ma et al., 2012).
Great Greeks like Socrates and Aristotle instigated an era in which emotions were viewed as antithetical to rational decision-making, but later research (Gupta, Koscik, Bechara, & Tranel, 2011) has shown that brain areas involved in emotion, like the amygdala and prefrontal cortex, are essential for decision-making. The Greeks were however not entirely in the wrong since damage to the prefrontal cortex, the rational center, can cause a hedonistic decision-mania (Van Horn et al., 2012). It is also true that people with damage to the amygdala, the emotion center, can be rendered incapable of decision-making (Gupta et al., 2011). An important function of the amygdala in our media context is that it associates incoming stimuli with an emotional value, in which e.g. a frightened person reading a newspaper is capable of incorporating the two.
Later researchers on emotions have long been divided into two groups; one proposing a dimensional view, while the other argues for a discrete conceptualization of emotions (Hamann, 2012). The dimensional perspective place emotions on a continuum, while discrete theorists apply distinct categories. Discrete perspectives have been previously validated in studies (Nabi, 2003) on emotions and framing effect, where the emotions themselves have been found to serve as frames for issues. Such findings, combined with others (Angie et al., 2011), legitimized our use of emotions as independent variable. Such debates are important since it concerns the accuracy of neuropsychological instruments measuring what causes and effects electro-chemical activity in the brain.
The aforementioned theoretical and empirical developments were necessary to underlie the rationale for why emotions are expected to play such a strong role in how a recipient is impacted by the framing effect, and further how news media “playing” on emotions can moderate the strength of these effects. Cassotti et al. (2012) have investigated the impact emotions have on this framing effect, and point out that little is known about the impact negative- or positive emotional stimuli has on this kind of bias. Nevertheless, they found that positive emotional context reduced risk propensity in a loss frame, eliminating the framing effect. They also confirmed that an affect heuristic belonging to System 1 causes framing effects. Affect heuristic refers to the tendency to improve judgmental efficiency by deriving both risk and benefit evaluations from effective reactions to the stimulus item (Pachur, Hertwig, & Steinmann, 2012). Affect heuristics have also been suggested by other researchers in similar studies (De Martino et al., 2006; Slovic, Peters, Finucane, & MacGregor, 2005).
Using a news story in a framing experiment has been done by researchers such as Gross and D’Ambrosio (2004). Tantalizingly, they found that manipulation of information available had an effect on which emotions the participants reported, though the difference in our experiments is that we will alter emotions before exposure to news stories. Kim and Cameron (2011) have conducted a similar experiment in which they found that which emotions a news frame induced, had a great influence on participants overall evaluation of corporate responses to crises. Researchers on emotions and framing have not used video-content as stimuli, to our knowledge, but that is something that we are going to do since its realism (Aron, Aron, & Jagiellowicz, 2012) can compensate for the potentially limited external validity of laboratory settings.
Relationship between the Variables
We investigate the cognitive mechanisms underlying framing effects, because researchers have argued that those who are resistant to framing are more likely to be competent decision-makers (Parker & Fischhoff, 2005). Before stating our hypotheses, we would like to present theories and research that can explain the relationship between thinking style, emotions, and framing effect in a media context.
Firstly, literature reviews have led researchers to conceptualize that framing may induce emotion, which in turn impinges on the level of cognitive effort (Dunegan, 1993) that subsequently shapes the framing effect (Kuo et al., 2009). The connection between thinking style and emotions has been theorized e.g. through the “cognitive-affective cost-benefit tradeoff model” (Gonzalez, Dana, Koshino, & Just, 2005). Researchers have theorized about the interplay between affect and cognition via showing that people generally try to minimize cognitive processing, but increases it when a problem induces negative feelings (Gonzalez et al., 2005). In addition, this interplay has been explicitly located by neuroscientists to the prefrontal cortex of the brain (Gray, Braver, & Raichle, 2002; Kuo et al., 2009; Wu, Zhang, Elieson, & Zhou, 2012). This stands in clear contrast with the traditional view that rationality should be considered independently of emotions (Hardman, 2009). Intuitive thinking styles have, in fact, been postulated to be shaped by emotionally significant past experience (Shiloh et al., 2002).
Morewedge and Kahneman (2010) explain how intuitive thinking evokes an automatic activation in memory which makes a foundation for interpreting a given situation. This interpretation is embedded in a previous context and incorporates appropriate emotions and preparedness for future actions. In some cases, this facilitates effective processes, while resulting in biases such as framing effects in others. This is called associative processing, and is based on the idea that a stimulus evokes memories, which in turn evoke emotions, which lastly evoke other reactions. Valence-based associative processing refers to positive labeling of an attribute, leading to an encoding of the information that tends to evoke favorable associations in memory. Negative labeling of an attribute, on the other hand, is more likely to cause an encoding that evokes unfavorable associations (Kuvaas & Selart, 2004). The essential feature of associative activation is its coherence; all elements are connected and yield a self-reinforcing pattern of cognitive, emotional, and physical responses (Morewedge & Kahneman, 2010). This representational difference is viewed as the cause of valence-consistent shifts in responses by some researchers (Levin et al., 1998).
Thinking style can be further understood by measuring a decision makers’ memory. Risky choices, for example, has been shown through imaging techniques to be associated with higher levels of brain activity in regions connected to the working memory (Gonzalez et al., 2005). Decision makers that received negatively framed information have shown tendencies to recall more information than decision makers receiving positively framed information. This suggests that negatively framed information triggers more careful, hence analytic thought than the positive one (Dunegan, 1993; Kuvaas & Selart, 2004; Ledgerwood & Boydstun, 2013).
With this knowledge fresh in mind, we assume that this strong connection between thinking style and emotions will play out in our experiment. We believe that a reliance on emotions and intuition after being exposed to a news story, will lead to the decision maker frequently falling prey to the framing effect. The opposite will be true for those who utilize a more thorough, analytic thinking style. In addition, we hypothesize that biased media coverage will do exactly this; play on emotions, and thereby help distort the truth in the direction desired by journalists. Based on this discussion, the following hypotheses are presented:
H1: Co-occurrence of positive emotions and high levels of intuitive thinking, causes participants to be more susceptible to framing effects in a news media context than co-occurrence of positive emotions and low levels of intuitive thinking.
H2: Co-occurrence of negative emotions and high levels of analytical thinking, causes participants to be less susceptible to framing effects in a news media context than co-occurrence of negative emotions and low levels of analytical state.
H3: Participants scoring high on analytical thinking are least likely to experience that emotions and news media context impact their susceptibility to framing effects.
Experimental Design and Procedure
A shortage on information about interaction effects in this field has been pointed out (Shiloh et al., 2002), and a reduced factorial design enables such measures in an economical and flexible way with sufficient statistical power (Collins, Dziak, & Li, 2009). These provisions contributes to strengthen our study. However, our measures are based on subjective and indirect measures, which potentially limits the validity. A possible solution to this could be measuring both variables through prohibitively expensive neuroimaging technologies. Other weaknesses concern issues such as social desirability bias and varying knowledge base.
Pre-test. Participants are to answer a survey before the experiment, in order to collect information about various factors that can impact the results we obtain; like gender, age, educational background, frequency of media news exposure, attitudes towards news outlets, emotional volatility.
Manipulation. We will randomly assign the participants to multiple experimental settings in order to establish and control for causal effects. Participants in the experimental conditions first receive a statement, either “Russian control over Crimea reduce risk of WW3” or “Russian control over Crimea increase risk of WW3”. Immediately after this, those receiving the positive frame will receive a positively framed movie clip aimed at evoking positive emotions, and vice versa; this would be a video adaptation of IAPS (Bradley & Lang, 2007). When measuring emotions, a combination of self-report (Watson, Clark, & Tellegen’s PANAS scale (1988)) and researcher observer ratings of participant behavior via webcam, will be conducted. Later, by the same valence based logic, news articles will be presented. The article they receive portray either a positive/optimistic (Peck, 2014) or negative/pessimistic (Schindler, 2014) angle on the Russia/Ukraine issue; both from highly respected news outlets. The control group will receive a “neutral” academic article discussing this conflict.
Post-test. Questions regarding participant’s evaluation of the news story and perceived risk of WW3 are given, in order to compare how framing distorts answers of the experimental group. They are also to reflect on their own thinking style and emotions experienced. To measure thinking style, we will immediately apply the widely used Rational-experimental Inventory (Epstein, Pacini, Denes-Raj, & Heier, 1996).
Angie, A. D., Connelly, S., Waples, E. P., & Kligyte, V. (2011). The influence of discrete emotions on judgement and decision-making: A meta-analytic review. Cognition & Emotion, 25(8), 1393-1422. doi: 10.1080/02699931.2010.550751
Aron, E. N., Aron, A., & Jagiellowicz, J. (2012). Sensory processing sensitivity: A review in the light of the evolution of biological responsivity. Personality & Social Psychology Review (Sage Publications Inc.), 16(3), 262-282. doi: 10.1177/1088868311434213
Borah, P. (2011). Conceptual issues in framing theory: A systematic examination of a decade’s literature. Journal of Communication, 61(2), 246-263. doi: 10.1111/j.1460-2466.2011.01539.x
Boydstun, A. E., & Glazier, R. A. (2013). A two-tiered method for identifying trends in media framing of policy issues: The case of the war on terror. Policy Studies Journal, 41(4), 707-736. doi: 10.1111/psj.12038
Bradley, M. M., & Lang, P. J. (2007). The International Affective Picture System (IAPS) in the study of emotion and attention. In J. A. Coan & J. J. B. Allen (Eds.), Handbook of emotion elicitation and assessment. (pp. 29-46). New York, NY US: Oxford University Press.
Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42(1), 116-131. doi: 10.1037/0022-35188.8.131.52
Cassotti, M., Habib, M., Poirel, N., Aïte, A., Houdé, O., & Moutier, S. (2012). Positive emotional context eliminates the framing effect in decision-making. Emotion, 12(5), 926-931. doi: 10.1037/a0026788
Chatterjee, S., Heath, T. B., Milberg, S. J., & France, K. R. (2000). The differential processing of price in gains and losses: The effects of frame and need for cognition. Journal of Behavioral Decision Making, 13(1), 61-75.
Collins, L. M., Dziak, J. J., & Li, R. (2009). Design of experiments with multiple independent variables: A resource management perspective on complete and reduced factorial designs. Psychol Methods, 14(3), 202-224. doi: 10.1037/a0015826
De Martino, B., Kumaran, O., Seymour, B., & Dolan, R. J. (2006). Frames, biases, and rational decision-making in the human brain. Science, 313(5787), 684-687. doi: 10.1126/science.1128356
Dunegan, K. J. (1993). Framing, cognitive modes, and image theory: Toward an understanding of a glass half full. Journal of Applied Psychology, 78(3), 491-503.
Dunham, W. R. (2013). Framing the right suspects: Measuring media bias. Journal of Media Economics, 26(3), 122-147. doi: 10.1080/08997764.2013.811587
Entman, R. M. (1993). Framing: Toward clarification of a fractured paradigm. Journal of Communication, 43(4), 51-58. doi: 10.1111/j.1460-2466.1993.tb01304.x
Entman, R. M. (2007). Framing bias: Media in the distribution of power. Journal of Communication, 57(1), 163-173. doi: 10.1111/j.1460-2466.2006.00336.x
Epstein, S. (1994). Integration of the cognitive and the psychodynamic unconscious. American Psychologist, 49(8), 709-724. doi: 10.1037/0003-066X.49.8.709
Epstein, S., Pacini, R., Denes-Raj, V., & Heier, H. (1996). Individual differences in intuitive–experiential and analytical–rational thinking styles. Journal of Personality and Social Psychology, 71(2), 390-405. doi: 10.1037/0022-35184.108.40.2060
Frisch, D. (1993). Reasons for framing effect. Organizational Behavior and Human Decision Processes, 54, 399-429.
Gonzalez, C., Dana, J., Koshino, H., & Just, M. (2005). The framing effect and risky decisions: Examining cognitive functions with fMRI. Journal of Economic Psychology, 26(1), 1-20. doi: 10.1016/j.joep.2004.08.004
Gray, J. R., Braver, T. S., & Raichle, M. E. (2002). Integration of emotion and cognition in the lateral prefrontal cortex. Proceedings of the National Academy of Sciences of the United States of America, 99(6), 4115-4120. doi: 10.2307/3058260
Gross, K., & D’Ambrosio, L. (2004). Framing emotional response. Political Psychology, 25(1), 1-29. doi: 10.1111/j.1467-9221.2004.00354.x
Gupta, R., Koscik, T. R., Bechara, A., & Tranel, D. (2011). The amygdala and decision-making. Neuropsychologia, 49(4), 760-766. doi: 10.1016/j.neuropsychologia.2010.09.029
Hamann, S. (2012). Mapping discrete and dimensional emotions onto the brain: Controversies and consensus. Trends in Cognitive Sciences, 16(9), 458-466. doi: 10.1016/j.tics.2012.07.006
Hammond, J. S., Keeney, R. L., & Raiffa, H. (2006). The hidden traps in decision making. Harvard Business Review, 84(1), 118-126.
Hardman, D. (2009). Judgment and decision making: Psychological perspectives. Cornwall: Blackwell Publishing.
Herring, E., & Robinson, P. (2003). Too polemical or too critical? Chomsky on the study of the news media and us foreign policy. Review of International Studies, 29(4), 553-568. doi: 10.2307/20097876
Hodgkinson, G. P., & Clarke, I. (2007). Exploring the cognitive significance of organizational strategizing: A dual-process framework and research agenda. Human Relations, 60(1), 243-255.
Igou, E. R., & Bless, H. (2007). On undesirable consequences of thinking: framing effects as a function of substantive processing. Journal of Behavioral Decision Making, 20(2), 125-142. doi: 10.1002/bdm.543
Kahneman, D. (2012). Thinking, fast and slow. London: Penguine Books.
Kane, J. E., & Webster, G. D. (2013). Heuristics and biases that help and hinder scientists: Toward a psychology of scientific judgment and decision making. In G. J. Feist & M. E. Gorman (Eds.), Handbook of the psychology of science. (pp. 437-459). New York, NY US: Springer Publishing Co.
Kennis, A. C. (2013). The media dependence model: An analysis of the performance and structure of U.S. and global news. (73), ProQuest Information & Learning, US. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=psyh&AN=2013-99031-118&site=ehost-live Available from EBSCOhost psyh database.
Kepplinger, H. M., Geiss, S., & Siebert, S. (2012). Framing scandals: Cognitive and emotional media effects. Journal of Communication, 62(4), 659-681. doi: 10.1111/j.1460-2466.2012.01653.x
Kim, H. J., & Cameron, G. T. (2011). Emotions matter in crisis: The role of anger and sadness in the publics’ response to crisis news framing and corporate crisis response. Communication Research, 38(6), 826-855. doi: 10.1177/0093650210385813
Kuo, F.-Y., Hsu, C.-W., & Day, R.-F. (2009). An exploratory study of cognitive effort involved in decision under framing: An application of the eye-tracking technology. Decision Support Systems, 48(1), 81-91. doi: 10.1016/j.dss.2009.06.011
Kuvaas, B., & Selart, M. (2004). Effects of attribute framing on cognitive processing and evaluation. Organizational Behavior & Human Decision Processes, 95(2), 198-207. doi: 10.1016/j.obhdp.2004.08.001
Kühberger, A. (1998). The influence of framing on risky decisions: A meta-analysis. Organizational Behavior & Human Decision Processes, 75(1), 23-55.
Ledgerwood, A., & Boydstun, A. E. (2013). Sticky Prospects: Loss Frames Are Cognitively Stickier Than Gain Frames. Journal of Experimental Psychology: General, 143(1). doi: 10.1037/a0032310
Levin, I. P., Schneider, S. L., & Gaeth, G. J. (1998). All frames are not created equal: A typology and critical analysis of framing effects. Organizational Behavior and Human Decision Processes, 76(2), 149-188. doi: 10.1006/obhd.1998.2804
Ma, Q., Feng, Y., Xu, Q., Bian, J., & Tang, H. (2012). Brain potentials associated with the outcome processing in framing effects. Neuroscience Letters, 528(2).
McElroy, T., & Seta, J. J. (2003). Framing effects: An analytic-holistic perspective. Journal of Experimental Social Psychology, 39(6), 610-617. doi: 10.1016/S0022-1031(03)00036-2
Morewedge, C. K., & Kahneman, D. (2010). Associative processes in intuitive judgment. Trends in Cognitive Sciences, 14(10), 435-440. doi: 10.1016/j.tics.2010.07.004
Nabi, R. L. (2003). Exploring the framing effects of emotion: Do discrete emotions differentially influence information accessibility, information seeking, and policy preference? Communication Research, 30(2), 224-247.
Noorzai, R. (2013). The role of media in the framing of the Afghan conflict and the search for peace. (74), ProQuest Information & Learning, US. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=psyh&AN=2013-99150-233&site=ehost-live Available from EBSCOhost psyh database.
Pachur, T., Hertwig, R., & Steinmann, F. (2012). How do people judge risks: Availability heuristic, affect heuristic, or both? Journal of Experimental Psychology: Applied, 18(3), 314-330. doi: 10.1037/a0028279
Parker, A. M., & Fischhoff, B. (2005). Decision-making competence: External validation through an individual-differences approach. Journal of Behavioral Decision Making, 18(1), 1-27. doi: 10.1002/bdm.481
Peck, M. (2014). 7 reasons why America will never go to war over Ukraine. Retrieved 26.3, 2014, from http://www.forbes.com/sites/michaelpeck/2014/03/05/7-reasons-why-america-will-never-go-to-war-over-ukraine/
Piñon, A., & Gambara, H. (2005). A meta-analytic review of framing effect: Risky, attribute and goal framing. Psicothema, 17(2), 325-331.
Plous, S. (1993). The psychology of judgment and decision making. USA: McGraw-Hill.
Reyna, V. F., & Brainerd, C. J. (1991). Fuzzy-trace theory and framing effects in choice: Gist extraction, truncation, and conversion. Journal of Behavioral Decision Making, 4(4), 249-262.
Rivers, W. L. (1991). The media as shadow government. In D. L. Protess & M. E. McCombs (Eds.), Agenda setting: Readings on media, public opinion, and policymaking. (pp. 153-160). Hillsdale, NJ England: Lawrence Erlbaum Associates, Inc.
Sanfey, A. G., & Chang, L. J. (2008). Multiple systems in decision making. In W. T. Tucker, S. Ferson, A. M. Finkel & D. Slavin (Eds.), Strategies for risk communication: Evolution, evidence, experience. (Vol. 1128, pp. 53-62). Malden: Blackwell Publishing.
Schindler, J. (2014). Retired Ukrainian General: Russia is ‘placing Europe on the verge of a third world war’. Retrieved 26.3, 2014, from http://www.businessinsider.com/john-schindler-ukrainian-general-putin-europe-world-war-iii-2014-3
Shiloh, S., Salton, E., & Sharabi, D. (2002). Individual differences in rational and intuitive thinking styles as predictors of heuristic responses and framing effects. Personality and Individual Differences, 32(3), 415-429. doi: 10.1016/S0191-8869(01)00034-4
Simon, A. F., Fagley, N. S., & Halleran, J. G. (2004). Decision framing: moderating effects of individual differences and cognitive processing. Journal of Behavioral Decision Making, 17(2), 77-93. doi: 10.1002/bdm.463
Simon, H. (1999). Bounded rationality and organizational learning. Reflections, 1(2), 17-27. doi: 10.1162/152417399570142
Slovic, P., Peters, E., Finucane, M. L., & MacGregor, D. G. (2005). Affect, risk, and decision making. Health Psychology, 24(4, Suppl), S35-S40. doi: 10.1037/0278-6133.24.4.S35
Smith, S. M., & Levin, I. P. (1996). Need for cognition and choice framing effects. Journal of Behavioral Decision Making, 9(4), 283-290. doi: 10.1002/(SICI)1099-0771(199612)9:4<283::AID-BDM241>3.0.CO;2-7
Stanovich, K., Toplak, M., & West, R. (2010). Contaminated mindware: Thinking biases of the cognitive miser. Rotman Management, 16-21.
Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4), 453-458.
Van Horn, J. D., Irimia, A., Torgerson, C. M., Chambers, M. C., Kikinis, R., & Toga, A. W. (2012). Mapping connectivity damage in the case of Phineas Gage. PLoS ONE, 7(5). doi: 10.1371/journal.pone.0037454
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063-1070. doi: 10.1037/0022-35220.127.116.113
Wegener, D. T., Petty, R. E., & Klein, D. J. (1994). Effects of mood on high elaboration attitude change: The mediating role of likelihood judgments. European Journal of Social Psychology, 24(1), 25-43. doi: 10.1002/ejsp.2420240103
Wong, K. F. E., Kwong, J. Y. Y., & Ng, C. K. (2008). When thinking rationally increases biases: The role of rational thinking style in escalation of commitment. Applied Psychology: An International Review, 57(2), 246-271. doi: 10.1111/j.1464-0597.2007.00309.x
Wu, Y., Zhang, D., Elieson, B., & Zhou, X. (2012). Brain potentials associated with the outcome processing in framing effects. International Journal of Psychophysiology, 85, 145–152.