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Facts Shape Feelings: Information, Emotions, and the Political Consequences of Violence

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Abstract

What makes violence political? Existing research argues that experiencing violence generates anger and grievances, which cause political mobilization, retribution, and spirals of escalating violence. I argue that the effect of violence on the political behavior of survivors is highly variable: situation-specific information shapes how survivors of violence experience anger, and whether they attribute blame to individual perpetrators or form more durable, expansive political grievances toward targets like police or prosecutors. I use qualitative and computational methods to analyze transcripts of original interviews with relatives of Black and Latinx homicide victims in Chicago, IL. Results show substantial diversity in emotional experience and blame attribution. I argue that this diversity is caused by variation in clarity about identity and motive of the perpetrator, and variation in perception of perpetrator responsibility. Having or lacking crucial information determines whether survivors become angry at perpetrators or form broader political grievances after traumatic experiences. Evidence from Chicago challenges the notion that violent trauma and anger have automatic or straightforward consequences for political behavior.

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Data availability

Data and replication code are available in the Political Behavior Dataverse (https://doi.org/10.7910/DVN/TD6YHR).

Notes

  1. I use the term “non-state” only to distinguish from police-perpetrated homicides. However, as Richie (2012) and Perry (2013) argue, it is difficult to characterize violence against racial minorities as decisively non-state given the state’s role in perpetuating conditions that make violence possible.

  2. Respondents were parents, guardians, or siblings of the victim.

  3. I chose not to “oversample” men to correct for this imbalance. Accordingly, the conclusions of this study are more likely valid for women’s behavior than men’s.

  4. I discuss how my identities as a researcher may have influenced this trend in Appendix F.

  5. One standard deviation ranges from “a little” angry to “quite a bit” angry. Average scores for “angry” alone are higher but the difference is not significant.

  6. STM is an improvement that incorporates document-level metadata into the model fit (Roberts et al., 2016).

  7. Topic models ignore semantic structure, so they incorporate vernacular and slang easily. For example, STM associates Chicago Survivors-specific terminology like “homegoing” (funeral) and “angel-day” (death anniversary) with other descriptors of funerals.

  8. The interviews are broken into 2300 paragraphs for model flexibility, but preserve correlation between paragraphs from the same interview via STM’s prevalence covariate functions. Topic correlations are reported at the paragraph level—i.e. ideas discussed together within a paragraph—whereas other associations are reported at the respondent level. The estimations of other associations propagate uncertainty from the model fit, which includes respondent ID as a covariate, into the (conservative) errors.

  9. Topic prevalence should be un-affected by crowding-out, i.e. talking more about one emotion automatically reducing discussion of another. All ten topics happen to be associated with one or more questions in the interview guide, and responses were not time-limited. Talking more about panic, for example, would never lead to “skipping” an opportunity to talk about anger.

  10. These approaches differ over whether different emotions are naturally separate phenomena (Lerner & Keltner, 2000), or a single integrated process (Barrett, 2006). The disagreement is not about empirical findings linking anger to risk assessment, attitudes, etc. so I refer to both approaches.

  11. Getting the attribution wrong is not an impediment to envisioning punishment (Clore & Gasper, 2000).

  12. Jackson (2019) shows that perception of inter-group threat (racist treatment by the state) in Chicago varies by gender: Men often downplay the threat of racism and women are more likely to express fear and anxiety.

  13. Ms. G accuses the perpetrators of a secondary wrong—what Fujii (2013) calls “extra-lethal” violence. She says that sometimes people “catch a bullet,” but is upset that someone “unloaded” a whole magazine into her son, who was likely not the intended target.

  14. I also interviewed Ms. H and her son Mr. H about the murder of a different son, killed by his girlfriend. Here, both were unequivocally angry at the girlfriend; as the cognitive clarity model predicts. This further suggests that “family” norms are an appropriate alternative explanation for Ms. H’s case.

  15. Chicago violence perhaps had a shared narrative in the past, but the breakdown of cohesive drug gangs since the 1980s has complicated the violence landscape (Stuart, 2020).

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Acknowledgements

Thank you to Fotini Christia, Stefano Costalli, Andy Halterman, Marika Landau-Wells, Rich Nielsen, Roger Petersen, Blair Read, Lily Tsai, Ariel White, and participants in the 2018 MIT Second Year Paper Workshop, MIT IR Works in Progress, the Harvard Working Group on Political Psychology, and MPSA 2019 for comments on prior drafts. Three anonymous reviewers and the editors of Political Behavior also provided valuable comments that have greatly improved this article. Ariel White provided excellent advice on interviewing survivors of trauma. JaShawn Hill, Susan Johnson, and other staff of Chicago Survivors not only made the interviews possible, but also provided extensive advice and logistical support. Steve Edwards provided valuable early advice on working in Chicago. Thanks finally to Sam Neal for tolerating me as a houseguest for the entirety of my time in Chicago. Data collection was approved by the MIT Committee on the Use of Humans as Experimental Subjects under protocol #1707023191.

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  1. Department of Political Science, Massachusetts Institute of Technology, Cambridge, MA, USA

    Aidan Milliff

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Milliff, A. Facts Shape Feelings: Information, Emotions, and the Political Consequences of Violence. Polit Behav 45, 1169–1190 (2023). https://doi.org/10.1007/s11109-021-09755-1

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