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TRANSCRIPT
Online Supplement for:What a Story?
Journalists’ Representation of Protests and Disorderly Gatherings, 1996-2007
Table of Contents:
Part 1: Analysis of the number of articles across event type
Part 2: Interactions of event type and key event features
Part 3: Controlling for newspaper characteristics
Part 4: Examining different lag structures for the number of previous events
Part 5: Diversity in protest claims
Part 6: Additional examples of media coverage of events
Part 7: List of newspapers used to sample protests, contentious protests, and CCIRs
Part 1: Analysis of the number of articles across event type
The dependent variable for this analysis is the count of unique newspaper articles for all protest
events (mean = 1.11 stories per event), contentious protests (mean = 1.24), and CCIRs (mean =
10.51). Since the distribution of the number of stories has a minimum value of one, we estimate
zero-truncated negative binomial regression to correct for the impossibility of zeroes. The
independent variables are operationalized identically to those in the main study. As we noted
above, CCIRs receive much greater attention than protest events, though part of this difference is
a consequence of our research design and the number of newspapers used to collect data on the
different types of events.
Results from the zero-truncated negative binomial regression analysis for each sample of
events are in Table OS1.1. Comparing across the models in the table, it is apparent that the
features of CCIRs themselves that drives much of the media interest in these events, particularly
their high level of destruction, the high prevalence of arrests, and their large size. There is an
interesting contrast for the effects of violence and property damage across the two types of
events. Violence is, not surprisingly, related to greater media coverage for protests, but not
CCIRs, while any property damage significantly increases attention for CCIRs but not protests.
Our reading of newspaper reports of CCIRs suggests that property damage is an important part
of the narrative; journalists often report in detail what was destroyed by participants and how
much damage occurred, and the overall level of destruction for CCIRs is significantly higher
compared to protests. For our sample of all protests, violence is very atypical, yet even in our
subsample of contentious protests—where violence and property damage occur much more often
—we see the same overall pattern of results.
Police arrests and use of force were more common during CCIRs, yet both predictors
were positive and significant for both types of protests. Indeed, there is a significant and negative
estimate for the police use of force for CCIRs. We suspect this is driven by the
institutionalization of protest that has occurred in Western democracies for the past 40 years.
Police are a common sight at protests, yet they generally take very little action. It is only when
they become involved in unusual ways (using force and making arrests) that journalists deem a
protest newsworthy. In contrast, police make arrests at over three-quarters of all CCIRs and use
force in almost half of them, so it seems reasonable to suspect that journalists view such
outcomes as a “normal” part of these gatherings. Last, it was clear during the coding process that
the scale of police responses to CCIRs was markedly different, and typically involved the
deployment of paramilitary units which quickly and aggressively ended the conflict. In turn, this
lessened the overall amount of property destruction taking place and ultimately made the event
less newsworthy. Finally, there is no evidence that prior events in the past thirty days increased
coverage for either type of event, nor do we see any effect for events occurring before or after
the 9/11 attacks. This suggests that reporters continued to treat overtly political events in the
same manner following the terrorist attacks of 9/11.
Overall, the results in Table OS1.1 point to a high level of comparability between both
types of protests we examine, supporting our argument that journalists have a relatively narrow
pattern of coverage for protest events. This pattern is markedly different compare to CCIRs.
A final component of our analysis of the number of articles devoted to events uses the
pooled sample approach described in Table 4 in the main manuscript. Here, we estimate a
negative binomial model rather than a zero-truncated negative binomial model as the latter did
not converge. Since the dependent variable has a lower boundary of 0, we subtracted 1 from the
story count for each event prior to analysis. We use two pooled samples, similar to Table 4: one
that combines all protest events and CCIRs, and a second that merges only contentious protests
and CCIRs. Similar to Table 4, the results in Table OS1.2 point to significant differences in how
newspapers cover each type of event that we examine. Specifically, holding all variables
constant, our model predicts that CCIRs have roughly 17 more stories for events when compared
to all protests, and nearly 56 more stories when compared to contentious protests.
Table OS1.1: Zero-truncated negative binomial predicting the number of articles covering protests (n=11,858), contentious protests (n=3115), and CCIRs (n=226).
AllProtests
ContentiousProtests CCIRs
Event CharacteristicsSize of Event 0.35*** 0.29*** 0.52***
(0.03) (0.03) (0.15)Violence 0.74*** 0.58*** 0.39
(0.14) (0.12) (0.33)Property Damage 0.20 0.22 1.58***
(0.17) (0.13) (0.26)Disruptive Actions 0.60*** 0.27** -0.02
(0.09) (0.10) (0.25)Police Actions
Arrests 0.78*** 0.45*** 0.97**(0.11) (0.11) (0.30)
Police Use of Force 0.29* 0.26* -0.69*(0.14) (0.13) (0.30)
Event SequencingEvent Count in Last 30 Days 0.01 0.01 -0.06
(4.40E-3) (4.60E-3) (0.22)After 9/11 0.05 0.02 -0.28
(0.08) (0.08) (0.24)
Intercept -5.47*** -3.12*** -1.86**(0.32) (0.27) (0.61)
Dispersion Parameter 0.81 0.87 0.29Model Chi-Square 508.48*** 221.92*** 66.68***Degrees of Freedom 8 8 8
Notes: Standard errors in parentheses; *p<0.05, **p<0.01, ***p<0.001
Table OS1.2: Negative binomial regression estimates predicting the number of stories for all protests and CCIRs (n=11,625) and contentious protests and CCIRs (n=3341)
All Protests &CCIRs
Contentious Protests &
CCIRsEvent Type
CCIR 3.26*** 3.16***(0.13) (0.13)
Event CharacteristicsSize of Event 0.36*** 0.31***
(0.03) (0.03)Violence 0.49*** 0.48***
(0.11) (0.11)Property Damage 0.67*** 0.67***
(0.11) (0.11)Disruptive Actions 0.40*** 0.24**
(0.08) (0.09)Police Actions
Arrests 0.86*** 0.58***(0.09) (0.10)
Police Use of Force -0.06 -0.12(0.12) (0.12)
PeriodAfter 9/11 0.02 -0.01
(0.06) (0.08)Number of Previous Events 0.01* 0.01
(3.93E-3) (4.85E-3)Intercept -3.85*** -3.29***
(0.10) (0.17)Overdispersion Parameter 0.59 0.63Model Chi-square 5888.48*** 2815.18***Degrees of Freedom 9 9
Notes: Standard errors in parentheses; *p<0.05, **p<0.01, ***p<0.001.
Part 2: Interactions of event type and key event features
This analysis extends the results in Table 4 by estimating interactions between our indicator for
CCIRs and our measures of police use of force, arrests, property damage, and participant-
initiated violence. We estimate models both dependent variables across the pooled sample of all
protests and CCIRs and the subsample of contentious protests and CCIRs. For the models
examining the number of unique adjectives of the number of stories, only the interactions
between CCIRs and the police use of force were statistically significant (p<0.05), though they
are negative. None of the interactions are significant for the model predicting the number of
dangerous descriptors using the pooled sample of all protests and CCIRs. Last, the data
combining contentious protests and CCIRs has two statistically significant interactions: a
negative effect for CCIRs and violence, and a positive effect for CCIRs and arrests. Overall, this
pattern of results indicates that it is not the specific attributes of CCIRs that result in departures
from scripts journalists rely on to describe protests, but the treatment of these events as a
different form of collective action.
Table OS2.1: Negative binomial regression estimates predicting the number of adjectives and the number of dangerous descriptors appearing in pooled coverage of events
All Protests &CCIRs Contentious Protests & CCIRs
# ofAdjectives
# of Dangerous Descriptors
# ofAdjectives
# of Dangerous Descriptors
Media AttentionNumber of Stories 0.13*** 0.10*** 0.08*** 0.07***
(2.17E-3) (4.70E-3) (2.29E-3) (3.63E-3)Event TypeCCIR 0.92*** 0.81** 1.01*** 0.96***
(0.13) (0.30) (0.14) (0.25)Event CharacteristicsSize of Event 0.11*** 0.17*** 0.18*** 0.16***
(0.01) (0.02) (0.01) (0.02)Violence 0.07 0.74*** 0.12** 0.80***
(0.04) (0.10) (0.05) (0.09)Property Damage 0.08 0.40*** 0.11* 0.44***
(0.05) (0.12) (0.05) (0.10)Disruptive Actions 0.21*** 2.25E-3 0.28*** 0.07
(0.02) (0.06) (0.04) (0.07)Police ActionsArrests 0.20*** -0.04 0.17*** -0.13
(0.03) (0.08) (0.04) (0.08)Police Use of Force 0.20*** 0.23* 0.17** 0.22*
(0.05) (0.11) (0.05) (0.10)PeriodAfter 9/11 0.10*** -0.02 0.11*** -0.16**
(0.02) (0.04) (0.03) (0.06)Number of Previous Events 0.03*** 0.02*** 0.03*** 0.03***
(1.10E-3) (2.64E-3) (1.79E-3) (3.27E-3)InteractionsCCIR * Violence -0.15 -0.50 -0.06 -0.55*
(0.15) (0.33) (0.16) (0.26)CCIR * Property Damage 0.06 -0.33 0.19 -0.23
(0.13) (0.28) (0.13) (0.23)CCIR * Arrests -0.02 0.51 0.08 0.64*
(0.14) (0.32) (0.15) (0.26)CCIR * Police Use of Force -0.34* -0.11 -0.33* -0.04
(0.14) (0.31) (0.15) (0.25)Intercept 1.20*** -1.34*** 0.97*** -1.31***
(0.02) (0.06) (0.06) (0.12)Overdispersion Parameter 1.71 0.37 1.55 0.62Model Chi-square 8087.45*** 1876.02*** 3736.34*** 1643.44***
Degrees of Freedom 14 14 14 14Notes: Standard errors in parentheses; *p<0.05, **p<0.01, ***p<0.001.
Part 3: Controlling for newspaper characteristics
Media coverage of events is shaped strongly by the organizations that produce them. For
instance, journalists employed by metropolitan newspapers may describe events in entirely
different terms than small-town newspapers. To further examine this possibility, we conducted
two sensitivity checks of our results. First, we built a including a variable for the average
circulation size of the newspapers covering the event. Second, we estimated fixed-effects
negative binomial models that cluster on newspaper (for the protest sample) or institution (for the
CCIRs sample). None of the effects for mean circulation are statistically significant at
conventional levels. As well, the fixed-effects models largely replicate our results reported in the
main manuscript. Overall then, our major substantive results were unchanged in these additional
tests. Tabular summaries of these analyses are in Table OS3.1 and Table OS3.2.
Table OS3.1: Negative binomial regression predicting adjective use and dangerous descriptors in media coverage of protests, contentious protests, and CCIRs.
Number of Adjectives Dangerous DescriptorsAll
ProtestsContentious
Protests CCIRsAll
ProtestsContentious
Protests CCIRsNewspaper Characteristics
Mean Circulation 0.109 0.101 -0.002 -0.053 0.009 0.163(0.103) (0.062) (0.060) (0.033) (0.052) (0.084)
Media AttentionNumber of Stories 0.635*** 0.559*** 0.043*** 0.604*** 0.605*** 0.046***
(0.018) (0.023) (0.002) (0.043) (0.042) (0.003)Event CharacteristicsSize of Event 0.074*** 0.136*** 0.078 0.144*** 0.121*** 0.118
(0.006) (0.011) (0.077) (0.016) (0.023) (0.104)Violence -0.040 0.006 0.233 0.651*** 0.707*** 0.434*
(0.041) (0.045) (0.160) (0.100) (0.090) (0.212)Property Damage -0.019 0.022 0.534*** 0.346** 0.389*** 0.427*
(0.048) (0.050) (0.127) (0.117) (0.098) (0.176)Disruptive Actions 0.157*** 0.225*** 0.094 -0.017 0.079 -0.328
(0.024) (0.036) (0.134) (0.062) (0.073) (0.183)Police Actions
Arrests 0.103*** 0.089* 0.261 -0.135 -0.218** 0.495*(0.030) (0.036) (0.150) (0.080) (0.078) (0.214)
Police Use of Force 0.137** 0.106* -0.043 0.168 0.145 0.459*(0.043) (0.050) (0.153) (0.109) (0.103) (0.208)
PeriodAfter 9/11 0.100*** 0.121*** 0.175 -0.020 -0.159* -0.045
(0.015) (0.029) (0.118) (0.039) (0.062) (0.160)Number of Previous Events 0.032*** 0.030*** 0.195* 0.023*** 0.030*** 0.105
(0.001) (0.002) (0.090) (0.003) (0.003) (0.120)Intercept -0.624*** -1.593*** 2.409** -1.141** -1.940** -2.037*
(0.159) (0.316) (0.749) (0.413) (0.671) (1.007)Dispersion 1.938 1.898 1.437 0.367 0.662 0.957
Notes: Standard errors in parentheses; *p<0.05, **p<0.01, ***p<0.001.
Table OS3.2: Fixed-effects negative binomial regression predicting adjective use and dangerous descriptors in media coverage of protests, contentious protests, and CCIRs.
Number of Adjectives Dangerous DescriptorsAll
ProtestsContentious
Protests CCIRsAll
ProtestsContentious
Protests CCIRsMedia Attention
Number of stories 0.372*** 0.328*** 0.014*** 0.318*** 0.278*** 0.016***(0.007) (0.010) (0.001) (0.019) (0.022) (0.002)
Event CharacteristicsSize of Event 0.08*** 0.131*** 0.156 0.129*** 0.137*** 0.191
(0.006) (0.010) (0.099) (0.013) (0.020) (0.117)Violence -0.040 0.019 0.574 0.691*** 0.769*** 1.056***
(0.035) (0.040) (0.362) (0.071) (0.075) (0.205)Property Damage 0.039 0.069 0.627*** 0.157* 0.192* 0.556**
(0.038) (0.043) (0.155) (0.073) (0.082) (0.200)Disruptive Actions 0.107*** 0.222*** 0.019 0.065 0.178** -0.413
(0.021) (0.032) (0.157) (0.049) (0.064) (0.221)Police Actions
Arrests 0.132*** 0.103** 0.137 0.028 -0.126 0.413*(0.026) (0.033) (0.179) (0.062) (0.069) (0.253)
Police Use of Force 0.204*** 0.131** -0.005 0.172 0.202 0.319*(0.034) (0.043) (0.185) (0.092) (0.115) (0.142)
PeriodAfter 9/11 0.098*** 0.132*** 0.312 -0.064* -0.137* 0.100
(0.014) (0.026) (0.229) (0.030) (0.055) (0.165)Number of Previous Events 0.021*** 0.020*** 0.253* 0.021*** 0.021*** -0.028
(0.001) (0.001) (0.104) (0.002) (0.003) (0.124)Intercept -0.301*** -0.757*** -1.547*** -2.088*** -1.917*** -1.743***
(0.025) (0.056) (0.356) (0.057) (0.115) (0.441)Notes: Standard errors in parentheses; *p<0.05, **p<0.01, ***p<0.001.
Part 4: Examining different lag structures for the number of previous events.
Throughout the manuscript, we used a 30-day lag period for the number of prior events. This
section of the Online Supplements provides additional analyses using 60-day and 90-day lag
periods as a sensitivity check. On the whole, there is substantial overlap between the results
using a 30-day lag and those based on 60-day and 90-day lags for both our analysis of adjectives
and the use of dangerous descriptors. One small difference between the results reported in Table
2 and Tables OS4.1 and OS4.2 is that the coefficient for police use of force is statistically
significant in the latter tables, while it is not in the former. Note that in Table 2, the effect has a T
statistics of 1.74, which is fairly close to a p<0.05 threshold. Further, the statistically significant
findings in Tables OS4.1 and OS4.2 point to a higher level of comparability between all protests
and contentious protests, which further supports our core argument. Overall, this is strong
evidence that our results are not an artifact of our 30-day lag window for the number of prior
events.
Table OS4.1: Negative binomial regression predicting adjective use in media coverage of protests, contentious protests, and CCIRs using 60- and 90-day lags in the number of previous events.
60-Day Lags 90-Day LagsAll
ProtestsContentious
Protests CCIRsAll
ProtestsContentious
Protests CCIRsMedia Attention
Number of stories 0.635*** 0.553*** 0.043*** 0.636*** 0.555*** 0.043***(0.018) (0.023) (0.002) (0.018) (0.023) (0.002)
Event CharacteristicsSize of Event 0.078*** 0.140*** 0.078 0.079*** 0.142*** 0.083
(0.006) (0.011) (0.077) (0.006) (0.011) (0.077)Violence -0.019 0.025 0.233 -0.029 0.016 0.247
(0.042) (0.046) (0.160) (0.042) (0.046) (0.161)Property Damage -0.027 0.010 0.534*** -0.038 -0.002 0.520***
(0.048) (0.050) (0.127) (0.049) (0.051) (0.128)Disruptive Actions 0.166*** 0.228*** 0.094 0.166*** 0.227*** 0.088
(0.024) (0.036) (0.134) (0.024) (0.036) (0.135)Police Actions
Arrests 0.140*** 0.126*** 0.261 0.151*** 0.134*** 0.274(0.031) (0.036) (0.150) (0.031) (0.037) (0.150)
Police Use of Force 0.164*** 0.118* -0.044 0.196*** 0.140** -0.065(0.043) (0.051) (0.152) (0.044) (0.051) (0.152)
PeriodAfter 9/11 0.101*** 0.132*** 0.175 0.106*** 0.136*** 0.142
(0.015) (0.029) (0.118) (0.015) (0.030) (0.117)Number of Previous Events 0.024*** 0.026*** 0.175* 0.018*** 0.020*** 0.167*
(0.001) (0.001) (0.089) (0.001) (0.001) (0.071)Intercept 0.672*** 0.490*** 2.383*** 0.65*** 0.449*** 2.421***
(0.029) (0.063) (0.287) (0.030) (0.064) (0.289)Dispersion 1.881 1.826 1.437 1.846 1.790 1.422
Notes: Standard errors in parentheses; *p<0.05, **p<0.01, ***p<0.001.
Table OS4.2: Negative binomial regression predicting dangerous descriptors in media coverage of protests, contentious protests, and CCIRs using 60-day and 90-day lags in the number of previous events.
60-Day Lag 90-Day LagAll
ProtestsContentious
Protests CCIRsAll
ProtestsContentious
Protests CCIRsMedia Attention
Number of stories 0.607*** 0.607*** 0.046*** 0.609*** 0.612*** 0.046***(0.044) (0.043) (0.003) (0.044) (0.043) (0.003)
Event CharacteristicsSize of Event 0.14*** 0.121*** 0.127 0.139*** 0.121*** 0.128
(0.016) (0.023) (0.105) (0.016) (0.023) (0.105)Violence 0.635*** 0.705*** 0.417* 0.624*** 0.692*** 0.415*
(0.101) (0.090) (0.204) (0.100) (0.09) (0.201)Property Damage 0.338** 0.383*** 0.422* 0.323** 0.364*** 0.406*
(0.117) (0.098) (0.178) (0.117) (0.098) (0.178)Disruptive Actions -0.030 0.066 -0.331 -0.027 0.068 -0.327
(0.062) (0.073) (0.185) (0.062) (0.073) (0.185)Police Actions
Arrests -0.116 -0.201* 0.488* -0.109 -0.191* 0.505*(0.079) (0.078) (0.215) (0.079) (0.078) (0.215)
Police Use of Force 0.117 0.177 0.428* 0.238* 0.198 0.412*(0.109) (0.103) (0.207) (0.109) (0.103) (0.206)
PeriodAfter 9/11 -0.007 -0.144* -0.070 -0.007 -0.139* -0.083
(0.039) (0.062) (0.159) (0.039) (0.062) (0.159)Number of Previous Events 0.015*** 0.022*** 0.150 0.011*** 0.017*** 0.094
(0.002) (0.003) (0.101) (0.002) (0.002) (0.094)Intercept -1.829*** -1.891*** -0.201 -1.848*** -1.922*** -0.171
(0.074) (0.127) (0.402) (0.075) (0.129) (0.402)Dispersion 0.364 0.650 0.938 0.364 0.645 0.933
Notes: Standard errors in parentheses; *p<0.05, **p<0.01, ***p<0.001.
Part 5: Diversity in protest claims and media attention
The protest data contained codes for 234 unique claims, which can be further reduced to 28
major families of claims (e.g., African American Civil Rights, Abortion, the Environmental
Movement, the Student Movement). Using these data, we built a new variable capturing claim
diversity for all protests and contentious protests. This variable is based on a count of the number
of unique claim families appearing in the prior 30 days of social movement mobilization in each
city. The results are summarized in Table OS5.1 below. The variables for claim diversity are not
statistically significant across the different model specifications. We also replicated this analysis
using 60-day and 90-day windows for claim diversity and the results were consistent with those
reported below.
Table OS5.1: Negative binomial regression predicting adjective use and dangerous descriptors in media coverage of protests and contentious protests using an additional measure of claim diversity.
Adjective Use Dangerous Descriptors
Claim DiversityNumber of Claims 0.007 0.021 0.002 0.042
(0.004) (0.076) (0.011) (0.026)Media Attention
Number of stories 0.632*** 0.552*** 0.604*** 0.604***(0.018) (0.023) (0.044) (0.042)
Event CharacteristicsSize of Event 0.079*** 0.14*** 0.139*** 0.118***
(0.006) (0.011) (0.016) (0.023)Violence -0.029 0.013 0.643*** 0.711***
(0.041) (0.045) (0.100) (0.090)Property Damage -0.021 0.014 0.347** 0.394***
(0.048) (0.050) (0.117) (0.097)Disruptive Actions 0.174*** 0.233*** -0.027 0.077
(0.024) (0.036) (0.062) (0.073)Police Actions
Arrests 0.121*** 0.118** -0.140 -0.224**(0.030) (0.036) (0.079) (0.078)
Police Use of Force 0.115** 0.085 0.180 0.141(0.043) (0.050) (0.109) (0.103)
PeriodAfter 9/11 0.092*** 0.114*** -0.009 -0.149*
(0.015) (0.029) (0.039) (0.062)Number of Previous Events 0.033*** 0.030*** 0.021*** 0.023***
(0.001) (0.002) (0.003) (0.004)Intercept 0.717*** 0.526*** -1.802*** -1.955***
(0.031) (0.065) (0.078) (0.134)Dispersion 1.920 1.864 0.367 0.667
Notes: Standard errors in parentheses; *p<0.05, **p<0.01, ***p<0.001.
Part 6: Additional examples of media coverage of events
Here we provide a more fine-grained analysis of media coverage across the different event types,
using articles covering two additional events as source material. As we show, coverage of these
events differed markedly in how they were framed by journalists. These differences in coverage
are consistent with our core argument that protest coverage is institutionalized, while media
coverage of CCIRs is not. Starting with protest events, one article, published by the Miami
Herald in April of 2000, covered demonstrations stemming from the forced deportation of Elian
Gonzales. After first noting that the protests were a product of “five months of pent-up passion,”
the story continued by noting:
Demonstrators, outraged at the seizure of Elian Gonzalez by a gun-toting federal SWAT team, shouted, wept, waved flags and signs and - in isolated angrier outbreaks - blocked traffic, threw rocks, overturned bus benches and torched tires and trash bins. Police met them fast and forcefully - some say too forcefully - pumping tear gas canisters into crowds and hauling off dozens in handcuffs. [Emphasis Added]
The article is clear in its emphasis that the violence and property destruction was atypical,
yet the lead also frames the story as the ‘angry outbreaks’ as perhaps following ‘pent-up
passion.’ This serves to add further legitimacy and justification to the protest, even
though it was marked by violence and property damage, and framed first using
conventional protest tactics such as signs, shouting, or public displays of emotions.
Journalists were generally much harsher in their characterization of CCIRs. One
incident occurring in 1999 at Michigan State University, was described by the Detroit
News as: “an estimated 5,000 to 10,000 rioters who started 61 fires, burned eight cars and
broke 24 windows.” The article extensively highlighted the irresponsibility of the
participants, noting that “They [students] proudly displayed empty tear gas canisters on
their balconies” in the aftermath of the event. The article also quoted a student who
stated: ““It was a blast in all senses of the word … We came together as a school, burned
some things, showed some skin and that’s fine. It was Spartan pride.” The article
contained multiple references to the extent of the damage and how despite preparations,
the police were overwhelmed by the throng of rioters. The Police Chief of East Lansing,
MI, noted that the crowd of participants was “one of pure hate ... that operated with an
intent to destroy.”
Such examples largely represent the differences in tone used by journalists to
describe the different types of events. Protests are treated as routine and predictable.
When deviations from the script occur, particularly when property damage or violence
takes place, many stories contextualize the violence within larger social issues or
otherwise emphasize the atypicality of the more contentious tactical forms. The opposite
is true for CCIRs, which are typically treated as examples of the ‘madding crowd’ and
hence, unpredictable in their wrath.
Part 7: List of newspapers used to sample protests, contentious protests, and CCIRs
Table OS7.1: Newspapers used to sample protests and contentious protestsNewspaper Name StateArizona Republic AZSan Francisco Chronicle CADenver Post COWashington Post DCFlorida Times-Union FLMiami Herald FLAtlanta Journal-Constitution GAChicago Tribune ILIndianapolis Star INThe Courier-Journal KYBoston Globe MADetroit Free Press MINew York Times NYThe Columbus Dispatch OHThe Oregonian ORPhiladelphia Inquirer PAThe Tennessean TNAustin American Statesman TXSeattle Post-Intelligencer WAMilwaukee Journal-Sentinel WI
Table OS7.2: List of newspapers used to sample CCIRsTitle State
Anchorage Daily News AKFairbanks Daily News-Miner AKJuneau Empire AKAnniston Star ALBirmingham News ALDaily Home ALDaily Mountain Eagle ALDaily Sentinel ALHuntsville Times ALTimes-Journal ALValley Times-News ALCourier ARMorning News of Northwest Arkansas ARPine Bluff Commercial ARSouthwest Times Record ARArizona Daily Star AZArizona Daily Sun AZArizona Republic AZArgus CABakersfield Californian CAContra Costa Times CADaily Breeze CADaily Democrat CADaily News of Los Angeles (Daily News) CADaily Review CADavis Enterprise CAFresno Bee CAHanford Sentinel CAInland Valley Daily Bulletin CALa Opinion CALake County Record Bee CALodi News-Sentinel CALong Beach Press-Telegram CAMadera Tribune CAMarin Independent Journal CAMerced Sun-Star CAModesto Bee CAMonterey County Herald CAOakland Tribune CAOrange County Register CAPasadena Star-News CAPress Democrat CAPress-Enterprise CA
Red Bluff Daily News CARedding Record Searchlight CARedlands Daily Facts CAReporter CASacramento Bee CASan Bernadino County Sun CASan Francisco Chronicle CASan Gabriel Valley Tribune CASan Jose Mercury News CASan Mateo County Times CASan Mateo Daily Journal CASanta Cruz Sentinel CASanta Maria Times CASiskiyou Daily News CATimes-Herald CATimes-Standard CATribune CATri-Valley Herald CAUkiah Daily Journal CAValley Times CAVentura County Star CAVisalia Times-Delta CAWest County Times CAWhittier Daily News CAConnecticut Post CODaily Camera CODaily Reporter-Herald CODaily Sentinel CODaily Times-Call CODenver Post COFort Morgan Times COGazette COJournal-Advocate COAdvocate CTChronicle CTGreenwich Time CTHartford Courant CTJournal Inquirer CTNew Haven Register CTNorwich Bulletin CTWaterbury Republican-American CTWashington Times DCWashington Post DCDelaware State News DEBradenton Herald FL
Charlotte Sun FLDaily Commercial FLDaytona Beach News-Journal FLEl Nuevo Herald FLFlorida Times-Union FLKey West Citizen FLMiami Herald FLNaples Daily News FLOcala Star-Banner FLOrlando Sentinel FLPalm Beach Daily News FLPalm Beach Post FLSarasota Herald-Tribune FLSouth Florida Sun Sentinel FLTampa Tribune FLAtlanta Journal-Constitution GAAugusta Chronicle GACherokee Tribune GAColumbus Ledger-Enquirer GADaily Tribune News GAGwinnett Daily Post GAMacon Telegraph GAMarietta Daily Journal GASavannah Morning News GAHonolulu Advertiser HIWest Hawaii Today HICreston News-Advertiser IAGazette IAHawk Eye IAQuad-City Times IATelegraph Herald IACoeur d'Alene Press IDIdaho Statesman IDLewiston Morning Tribune IDTimes News IDBeacon News ILBelleville News-Democrat ILBreeze-Courier ILChicago Sun-Times ILChicago Tribune ILCourier ILCourier News ILDaily Herald ILEdwardsville Intelligencer ILHerald & Review IL
Herald News ILJournal Gazette ILNews-Gazette ILNewsTribune ILNorthwest Herald ILPantagraph ILPeoria Journal Star ILRegister-Mail ILRockford Register Star ILSouthern Illinoisan ILState Journal-Register ILTimes-Courier ILChronicle-Tribune INCommercial Review INEvansville Courier & Press INHuntington Herald-Press INIndianapolis Star INJournal Gazette INMadison Courier INNews-Sentinel INPost-Tribune INVincennes Sun-Commercial INAbilene Reflector-Chronicle KSChanute Tribune KSDodge City Daily Globe KSEmporia Gazette KSGarden City Telegram KSHays Daily News KSHutchinson News KSManhattan Mercury KSMorning Sun KSNewton Kansan KSOttawa Herald KSParsons Sun KSSalina Journal KSTopeka Capital-Journal KSWichita Eagle KSCourier Journal KYDaily News-Bowling KYDaily News-MiddlesBoro KYHarlan Daily Enterprise KYLexington Herald-Leader KYOwensboro Messenger-Inquirer KYAdvocate LATimes-Picayune LA
Berkshire Eagle MABoston Globe MABoston Herald MACape Cod Times MAEnterprise MANorth Adams Transcript MAPatriot Ledger MARecorder MASentinel & Enterprise MASun MAWorcester Telegram & Gazette MACapital MDSun MDBangor Daily News MEKennebec Journal MEMorning Sentinel MEPortland Press Herald/Maine Sunday Telegram 2 titles MEAnn Arbor News MIBay City Times MIDetroit Free Press MIDetroit News MIFlint Journal MIGrand Rapids Press MIHillsdale Daily News MIHolland Sentinel MIHuron Daily Tribune MIJackson Citizen Patriot MIKalamazoo Gazette MILudington Daily News MIMidland Daily News MIMuskegon Chronicle MISaginaw News MITimes Herald MIDuluth News-Tribune MNSt. Paul Pioneer Press MNStar Tribune: Newspaper of Twin Cities MNHannibal Courier-Post MOJefferson City News-Tribune MOJoplin Globe MOKansas City Star MOMonett Times MOSt. Joseph News-Press MOSt. Louis Post-Dispatch MOBolivar Commercial MSClarksdale Press Register MS
Delta Democrat Times MSGreenwood Commonwealth MSSun Herald MSBozeman Daily Chronicle MTCharlotte Observer NCCourier-Tribune NCDaily Advance NCDaily Courier NCDaily Dispatch NCDaily Reflector NCFayetteville Observer NCHerald-Sun NCMorning Star NCNews & Observer NCNews & Record NCRichmond County Daily Journal NCRobesonian NCRocky Mount Telegram NCSalisbury Post NCWinston-Salem Journal NCBismarck Tribune NDGrand Forks Herald NDGrand Island Independent NELincoln Journal Star NEYork News-Times NEConcord Monitor NHNew Hampshire Union Leader/New Hampshire Sunday News NHTelegraph NHBurlington County Times NJGloucester County Times NJJersey Journal NJNews of Cumberland County NJPress of Atlantic City NJRecord NJStar-Ledger NJTimes NJToday's Sunbeam NJTrentonian NJAlamogordo Daily News NMAlbuquerque Journal NMCarlsbad Current-Argus NMDaily Times NMLas Cruces Sun-News NMRoswell Daily Record NMSanta Fe New Mexican NM
Las Vegas Review-Journal NVBuffalo News NYDaily Gazette NYDaily Messenger NYDaily News NYNew York Daily News NYNew York Post NYNew York Sun NYNew York Times NYObserver-Dispatch NYPost-Standard NYRecord NYSaratogian NYStaten Island Advance NYTimes Union NYWatertown Daily Times NYAkron Beacon Journal OHBlade OHColumbus Dispatch OHCourier OHDayton Daily News OHJournalNews OHLima News OHMiddletown Journal OHPlain Dealer OHRepository OHReview Times OHSpringfield News-Sun OHAltus Times OKBartlesville Examiner-Enterprise OKDaily Ardmoreite OKDurant Daily Democrat OKLawton Constitution OKMiami News-Record OKMuskogee Daily Phoenix and Times-Democrat OKOklahoman OKTulsa World OKBulletin ORDaily Astorian ORDalles Chronicle OREast Oregonian ORHerald and News OROregonian ORRegister-Guard ORWorld OR
Bucks County Courier Times PACentre Daily Times PADaily Courier PADaily News (Lebanon) PADelaware County Daily Times PAErie Times-News PAEvening Sun PAExpress-Times PAHerald-Standard PAIntelligencer Journal PAIntelligencer Record PALancaster New Era PALeader Times PAMercury PAMorning Call PANew Castle News PAObserver-Reporter PAPatriot-News PAPhiladelphia Daily News PAPhiladelphia Inquirer PAPhoenix PAPittsburgh Post-Gazette PAPublic Opinion PAReporter PAStandard-Speaker PATimes Leader PATribune-Review PAValley Independent PAValley News Dispatch PAYork Daily Record/York Sunday News PAYork Dispatch PAWesterly Sun RIAnderson Independent-Mail SCHerald SCHerald-Journal SCPost and Courier SCState SCSun News SCTimes and Democrat SCAberdeen American News SDCleveland Daily Banner TNCommercial Appeal TNDaily Times TNGreeneville Sun TNHerald-Citizen TN
Knoxville News-Sentinel TNOak Ridger TNTennessean TNAbilene Reporter-News TXAmarillo Globe-News TXAustin American-Statesman TXBaytown Sun TXBeaumont Enterprise TXBrazosport Facts TXCorpus Christi Caller-Times TXDaily Sentinel TXDallas Morning News TXDel Rio News-Herald TXDenton Record-Chronicle TXEagle TXEl Paso Times TXFort Worth Star-Telegram TXGalveston County Daily News TXHerald Democrat TXHouston Chronicle TXKerrville Daily Times TXLongview News-Journal TXLubbock Avalanche-Journal TXLufkin Daily News TXMarshall News Messenger TXMidland Reporter-Telegram TXNew Braunfels Herald-Zeitung TXOdessa American TXParis News TXPlainview Daily Herald TXSan Angelo Standard-Times TXSan Antonio Express-News TXSeguin Gazette-Enterprise TXVictoria Advocate TXWaco Tribune-Herald TXWaxahachie Daily Light TXWichita Falls Times Record News TXDeseret News UTHerald Journal UTSalt Lake Tribune UTStandard-Examiner UTDaily News-Record VADaily Press VAFree Lance-Star VAProgress-Index VA
Richmond Times-Dispatch VARoanoke Times VAVirginian-Pilot VAWinchester Star VABennington Banner VTBrattleboro Reformer VTCaledonian-Record VTRutland Herald VTTimes Argus VTBellingham Herald WAChronicle WAColumbian WADaily Record WADaily World WAKitsap Sun WANews Tribune WAOlympian WASeattle Post-Intelligencer WASeattle Times WASpokesman-Review WAYakima Herald-Republic WAMilwaukee Journal Sentinel WIWaukesha Freeman WIWisconsin State Journal WICharleston Daily Mail WVCharleston Gazette WVHerald-Dispatch WVWyoming Tribune-Eagle WY