EVIDENCE FROM THE 2020 SUMMER BLM PROTEST
1.5 Discussion
model, it can be seen that changing an individuals interest from 0 to 1 causes a 9%
increase in the probability that they protest, while changing the identity score from 0 to 1 has a 1.4% increase in the probability of protesting. The substantive result for political interest is robust controlling for identity. This robustness supports the notion that conflating identity and interest would produce substantively different re- sults. These results support Hypothesis 1, that individuals with higher signal levels are more likely to protest, for both signal types. The result is stronger for interest than identity. This is counter to the expectation given existing literature which in general suggests that collective identity is a major driver for political participation.
This evidence together supports the supposition that researchers that conflate iden- tity for interest dramatically overestimate the effects of identity on protest behavior.
In assuming that interest was collective identity, other researchers may easily have biased results.
Table 1.6: APEs for logit model with daily fixed effects
(1) (2) (3)
Identity 1.4∗ 2.1∗∗
(0.7) (0.7)
Interest 9.1∗∗∗ 9.2∗∗∗
(1.4) (1.4)
Chicago −5.5∗∗∗ −5.4∗∗∗ −5.5∗∗∗
(1.3) (1.3) (1.3)
Houston −6.0∗∗∗ −5.8∗∗∗ −5.9∗∗∗
(1.5) (1.5) (1.5)
Observations 17,782 17,782 17,782
∗p<0.1;∗∗p<0.05;∗∗∗p<0.01
Note: The model was estimated using a probit instead of a logit and with various interaction terms to test for the validity of pooling—the results remained consistent. In addition the data is truncated to only include individuals who tweet during more than 3,5, and 7 protests and the results do not change significantly.
previous studies of mobilization using online data by separately operationalizing interest and identity. Previous work assumes that an account using a hashtag or certain images identifies with the movement with which those trackable entities are associated. This assumption is too broad and likely explains why this chapter finds results different from previous studies using digital trace data.
Using this operationalization of both values, we find new results which differ from past research. We find that individuals are more likely to protest given higher levels of interest and slightly more likely to protest given higher levels of collective identity. One of our most interesting results is that interest levels increase the day of a protest and peak the day after, before slowly returning back to base levels. This suggests that the effect of the protest is more transient and less longstanding. These results suggest a minimal impact of collective identity on protesting and protesting on collective identity.
By improving the measurement of identity with online data, we build on previous quantitative, non-social media research into identity and collective action in several ways. Collective identity is salient during the mobilization process in authoritarian settings (Pearlman, 2018; Pfaff, 1996). This contrast with the 2020 BLM protests suggests that identity may be less salient in settings where citizens have other means of of organizing. In settings such as the United States, identity may therefore not be an axis on which to build boundary-spanning movements (Wang et al., 2018). The difficulty of mobilizing around identity is further heightened when the identity is race and there are prevailing biases against the group mobilizing (Manekin & Mitts, 2022)
In previous research, the use of surveys leads to biases in both selection and response (Westwood et al., 2022). The spontaneous nature of protests, in addition, makes pre-measurement difficult and, in most cases, impossible (Chenoweth et al., 2022).
In our research, these issues are not as problematic. The frequent use of social media by many members of society provides researchers a window into the minds, and histories, of individuals. In using social media the probability of bias is minimized as individuals cannot retroactively add tweets and are not aware they are being observed for this purpose. We have argued that, previous research using social media data has defined collective identity too broadly. In following the usage of hashtags and other trackable symbols, the quantity measured has instead evolved into interest rather than collective identity.
Moving forward, there are three avenues of future research to pursue. In order to further validate the results found in this chapter, measuring interest and identity for other social movements should be performed. Other movements, such as the Yellow Vests in France, have different contexts and can be used to see if our results are general or specific to the Black Lives Matter movement. The second extension is to include individuals who did not protest as a baseline in order to see if there are clear differences in the interest and identity of those who protest and those who never protest. Third, online identity appears highly salient in motivating changes in online behavior (Munger, 2016; Siegel & Badaan, 2020; Taylor et al., 2022). This chapter’s results suggest that identity is less important in changing offline protest behavior, and future work should continue to explore the differential effects of identity.
This chapter provides a framework in which to study protest movements and indi- vidual signals of collective action. It enables the contextualization of much of the previous quantitative work on the subject and takes a step towards unifying it into a singular conversation. While there is clear future work to be done, this chapter provides a first step in these efforts.
C h a p t e r 2