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Blogging Ferguson in Black and White
Douglas L. Mendenhall, PhD (bio)
Abilene Christian University
Instructor/Journalist in Residence
Department of Journalism and Mass Communication
Abilene Christian University
Author
Note
Suggesting this study
and assisting with its data collection were 47 undergraduate students enrolled
in Media Issues, the introductory course within the ACU Department of
Journalism and Mass Communication. They were supervised by Jessica Clark.
Abstract
Blog posts and appended comments
about the shooting of a black teen in Ferguson, Missouri, are analyzed for differences
based on the race of the authors. Using Diction 7.0, a common word-counting
program, seven differences are seen, with black-authored posts higher in
commonality, cognition, hardship, human-interest, satisfaction, and
self-reference, while white-authored posts are higher in use of collectives.
From a social identity perspective, tonal differences do not appear to constitute
differing levels of incivility.
Keywords:
Ferguson, race, blogs, Diction 7.0, incivility, social identity theory
Blogging
Ferguson in Black and White
Online responses to the August 2014
shooting death of Michael Brown in Ferguson, Missouri, can be seen as a virtual
continuation of the racial divisions and tensions that erupted after this
African-American teenager was shot by a white police officer. Eclipsing even
“The Ice Bucket Challenge,” Ferguson immediately became the most discussed news
story in the United States (Halimi,
2014), as protests and other developments filled newspapers, television
networks, online sites and social media with facts, speculation, analysis, and
comments. As with earlier race-based news juggernauts in the United States,
such as the cross-racial homicides involving O.J. Simpson in 1994 and George
Zimmerman in 2012 (Blow,
2012), whites and blacks quickly developed “a war of competing narratives”
(McClune,
2014) around news from Ferguson.
The present study seeks to examine
how black and white writers expressed their opinions about Ferguson on the
Internet’s most popular political blogs, specifically looking for differences
in the tone of their messages. The study examines the tone not only of blog
posts but also of the comments appended to them to see whether black and white
authors elicited differently toned responses. These analyses are made with the
use of Diction 7.0, a widely applied software package that offers a
quantitative method for assessing the tone of any written message by searching
for and measuring dozens of semantic features. While a simple tally would be
sufficient to test whether whites and blacks lined up on different sides in
discussing the altercation between Michael Brown and Officer Darren Wilson,
this study seeks to go deeper and probe what differences can be seen in the
tone of the messages with which they expressed their positions. Also, with
roughly two-thirds of each of the past four generations—Millenials, Gen Xers, Baby
Boomers, and the Silent Generation—agreeing that “Incivility in America has
risen to crisis levels” (Weber
Shandwick, Powell Tate, 2014, p. 3) and even greater numbers agreeing that
online social media including blogs encourage incivility (p. 9), this study
will ask whether racial differences emerge in the levels of uncivil language
used by black and white bloggers.
Literature
review
Cyberspace represents a roughly
level playing field for studying differences in message tone along racial
lines. The most recent Pew survey finds that in most categories Internet use
among African-Americans is equivalent to that of whites, with black representation
higher than white in certain social networking platforms such as Twitter (Smith,
2014) and with the continuation of a trend first identified in 2009 of blacks
using smart phones at a higher rate than whites (Smith, 2010).
Across a spectrum of online activities that includes blogging, blacks and other
minority groups were found to be more active in the creation of content, with
the enhancement of social identity identified as a primary motivation for such
creation (Correa & Jeong, 2011). Furthermore, Daniels (2013) notes that
blogging by African-Americans and other minorities can allow for the building
of “diasporic communities” in which the members shape one another and their
scattered audiences (p. 9).
Such findings pave the way for the use of social identity
theory as a perspective from which to consider the Ferguson blogs. This
explanation rises from a general assumption permeating social psychology that while
individual behavior is wrapped up in the human search for personal meaning, this
often happens within group settings (Tajfel & Turner, 1979). People who satisfy
one another’s needs and who expect to achieve satisfactions from their
association quickly develop feelings of mutual attraction and hence become a
group (Turner et al., 1987).
Refinement of this theory by Abram and Hogg (1988) led to
the eventual suggestion that, “Social identity and intergroup behavior is
guided by the pursuit of evaluative positive social identity through positive
intergroup distinctiveness, which in turn is motivated by the need for positive
self-esteem” (Hogg & Terry, 2000, p. 124). In other words, individuals
prefer to view themselves as part of a group that represents the most
personally advantageous association they could have made. They gain self-esteem
from group esteem and will therefore work harder to see their chosen group
succeed (Derks, van Laar, & Ellemers, 2009).
One way to increase such gratification is to maximize the
distance between the “in” (or self-identified) and “out” groups (Tajfel &
Turner, 1979). That is, we enhance our own group to increase our own self-worth
and inherently seem to believe that pushing other groups down elevates our own (Platow
et al., 1999). Furthermore, an individual tends to identify with a group and
judge others by their group traits rather than by their individual traits more
during a time of threat to the in-group’s social identity (Branscombe &
Wann, 1994). In some cases, outright racism can result from such social
identification, as entire sectors of a society are judged as a group based on
skin color or ethnicity (Tajfel & Turner, 1979). Yet a clear marker such as
skin color is not required: Early experiments (Tajfel, 1970, 1981, 1982; Tajfel
& Turner, 1979) suggest that group identification and preference can be
triggered even by something as minimal as giving a common but meaningless label
to a subset of a large group. The salience and strength of this
self-identification with a group is seen to rise and fall depending on external
pressures (Huddy, 2001).
One stream of research using social identity theory has
focused on how individual and group identities are created, manipulated, and
used in online communication given the ease with which users can shield their
personal information. Internet participation also brings into play certain
commonalities, breaking participants into groups along lines of gender, age, race,
and differentiations in the amount and intensity of their online use (King,
2001) that allow for similar affective responses throughout the Internet
audience, and creating different types of public space depending on the group
identities employed there. Visual anonymity, rather than interfering with the
processes of SIT, has been found to directly increase an online participant’s
attraction to a group and indirectly increases that participant’s positive
stereotyping of the group (Lea, Spears, & de Groot, 2001). Consequent
research suggests that this tugging toward a group caused by online anonymity
can even overcome individual personality traits (Lee, 2006). Predating social
identity theory—and the flaming Internet by almost a century—is a strangely
relevant perception about ethnocentrism actually being an expression of
self-love at a group level: “The insiders in a we-group are in a relation of
peace, order, law, government, and industry to each other. Their relation to
all outsiders, or others-groups, is one of war and plunder, except in so far as
agreements have modified it” (Sumner, 1906, p. 12).
Consistent with this line of
thinking, in times of war, plunder, and other major disturbances SIT would
predict clearly defined differences between two groups of bloggers—and evidence
to support such a perspective is indeed available along racial dividing lines.
For example, one researcher cites major themes of racial inequity and white
privilege within the stream of blogs and other Internet messages from
African-American authors in the disturbing wake of Hurricane Katrina,
exemplified by a post headlined, “Nobody gets out of here who’s not white” (Brock, 2008, p. 14), that spoke
to concerns about inequities in the evacuation of New Orleans. Demonstrating a
different type of racial difference during a different type of crisis, authors
within an African-American blog community were found to utilize within their
posts about the effects of the AIDS epidemic at least three traditional black
communication conventions: interaction, communal support, and kinesics—body
movements including dancing and singing (Kvasny & Igny, 2008, p. 584). Another
researcher found that black-authored blogs represent a unique opportunity to
enhance discussions about niche topics such as health concerns that primarily
affect African-Americans (Della, Griffin, Eroğlu, Bernhardt, & Wells,
2013). Thus, the literature suggests that times of stress often bring out
racially focused differences in the blogosphere. Furthermore, when such online
differences are expressed with uncivil language on blog sites, it can have a
“nasty effect” that results in increased polarization of groups within the audiences
(Anderson, Brossard, Scheufele, Xenos, & Ladwig, 2014).
As for what is
achieved by such racially distinctive message creation, many researchers have
concluded that refining social identity through Internet participation can for
African-Americans be a positive step in dealing with societal inequities. “Much
like the world offline, participating in online cultural communities will help
them to develop a healthy sense of racial identity, what psychologists argue is
necessary to resist the pernicious effects of racism” (Byrne, 2008, p. 33).
This group social identity also can be seen in the finding that black readers
browsing a news site were more likely to select both positively and negatively
valenced stories about their own race, but only negatively valenced stories
about their racial outgroup—a habit not shared by white readers in the study
(Appiah, Knobloch-Westerwick, & Alter, 2013).
Thus, SIT
suggests that in the wake of the Michael Brown shooting in Missouri, we can
expect to see increased salience for group identities built along racial lines.
The present study chooses to focus on the blogosphere to study possible differences
in how these racial groups express themselves because the diffusion of the
Internet offers a potential for minority authors to speak as often as they wish
that can be lacking in the more traditional media realm, where for example only
4% of the books reviewed by a recognized progressive outlet such as the New
York Times are written by Africans or African-Americans (Gay, 2012). Online,
such a lag for black voices is less of a problem. Schradie (2011) reports that
lower educational levels still serve as a barrier to the ability of
African-Americans to blog, but notes that once they overcome this barrier and
gain online access, blacks blog at a higher rate than whites with access.
Admittedly, even if, as Schradie suggests, this difference is based on socio-economic
factors rather than race, it may bring with it the problem of African-American
bloggers being limited in their ability to reach beyond their silos and speak
to working-class blacks or to broader white audiences. Because of that
limitation, comparing the sizes of the actual audiences reached by black and by
white bloggers is mostly beyond the scope of this study, which will be limited
to comparing the tone of the messages offered for consumption.
Thus, the
current study of Ferguson-related online messages attempts to shed light on
three main questions:
RQ1:
In what ways if any does the tone of messages created by white authors differ
from the tone of messages created by black authors as they comment on a
sensitive, race-related current event?
RQ2:
In what ways if any does the tone of reader responses to white authors differ
from the tone of reader responses to black authors?
RQ3:
Are different levels of incivility apparent in the tone of messages created by
black and by white authors?
Methodology
Diction 7.0 provides a stable,
quantitative look at what is usually a more nuanced, qualitative undertaking:
understanding the tone of a mass media message that builds from the
connotations of each word selected and positioned by an author. An established
research guideline is that the use of computers as an aid for content analysis
should be limited to cases in which this will produce valid measures, reduce
the study’s cost, and improve reliability (Riffe, Lacy, & Fico, 2005). Diction
7.0 software offers a scientific method for quickly measuring the tone of a
written message by searching for and measuring dozens of semantic features. The
software employs 31 non-overlapping, internal dictionaries that define the conceptual
categories. The software computes quantitative scores for these categories
based on the content properties of the texts in question. Moreover, scores for these
categories are combined and subjected to mathematical functions to yield
composite scores for some variables of interest, including the five “Master
Variables” of activity, optimism, certainty, realism, and commonality. Diction
7.0 relies on a 10,000-word search routine that can be used with any kind of
English-language texts. Scholars have employed Diction to examine a variety of
topics across numerous communication contexts (Young & Soroka, 2012). A
recent example is Political Tone: How Leaders Speak and Why (Hart,
Childers, & Lind, 2013), co-authored by one of the developers of Diction. Political
Tone uses the word-counting software to reveal the overall tone of
contemporary political messages, asserting that tone consists of “(1)
individual word choices that (2) cumulatively build up (3) to produce patterned
expectations (4) telling an audience something important (5) about the author’s
outlook on things” (p. 12) and using that template to calculate and differentiate
between what constitutes, for instance, an overall “Democratic” tone or
“Republican” tone (p. 71). Other examples of researchers applying Diction
include analyses of the tone of campaign speeches by winning U.S. presidential
candidates (Lowry & Naser, 2010), of differences between the rhetoric at
local and national Promise Keepers events (Eidenmuller, 2002), of media
coverage of the 9/11 terror attacks (Cho et al., 2003), of the comparative
optimism of governors and presidents (Crew and Lewis, 2011), and of the use of
power in the speeches of Adolf Hitler and Martin Luther King Jr. (Robinson
& Topping, 2012). These studies and others demonstrate the broad acceptance
of Diction within the communication discipline as an appropriate tool for
comparison of tone within categories of messages such as those to be gathered
from popular blog sites for the current study.
At a small southwestern college, 47
students in a beginning mass media course worked in three-person teams to
collect Ferguson-related blogs published from August 9 to August 23,
representing the first two weeks following the shooting death of Michael Brown.
A team was assigned to each of the 15 most popular political websites in the
United States (eBizMBA.com, October 2014) and instructed to save up to 100 random,
Ferguson-related blog posts as well as the first 20 comments appended by
readers of each blog post. Sites included in the study are, in order of their
popularity: Huffington
Post, The Blaze, Drudge Report, News Max, Politico,
Salon, Info
Wars, Brietbart, Daily Caller, Washington Times, Christian Science Monitor, WND, Daily Kos, Think Progress, and Town Hall. Because of the immensity of the
Huffington Post site and to increase the number of black-authored posts,
collection there was limited to the “Black Voices” section. Posts were
converted to text files and efforts were made to categorize their authors by
race using an accompanying photograph or biography. Several more authors were
categorized after employing a search engine to seek more personal information
about them. Blog posts for which the author’s racial category could not be
determined were eliminated from the sample. Finally, all remaining files were
vetted to eliminate those that consisted of traditional news stories, leaving
only those that consisted of commentary or opinion. This resulted in a sample
frame of 157 blog posts, of which 119 were identified as having white authors
and 38 as having black authors. Also collected were 114 sets of up to the first
20 comments appended to these blog posts, including 86 sets from white-authored
posts and 28 sets from black-authored posts. The standard message length for
Diction analysis is 500 words, so the first 20 comments on a post were
considered as a single message to avoid the inability to individually assess
the many brief comments. Several blog sites did not allow comments or had removed
them from their site by the time collection was attempted in September and
October. Each of the 271 collected files was analyzed using Diction 7.0 and
transferred to SPSS.
Results
Splitting the 157 blog posts by
the race of the authors, one-way ANOVAs were used to compare mean scores for
each of the 35 Diction variables, the five Diction Master Variables calculated
using combinations of those variables, and a variable constructed to indicate
the use of 20 vulgar or profane words commonly found on Internet sites
according to two studies (Kirk,
2013; GFK
Group, 2013).
Answering RQ1 in the affirmative, significant
differences in the tone of white- and black-authored messages were found in seven
variables at the level of p < .05, as displayed in Table 1 and Table
2. The measured variable was significantly higher for black-authored messages
in these six instances: cognition (p = .01), commonality (p =
.02), hardship (p = .02), human interest (p = .002), satisfaction
(p = .03), and self-reference (p = .001). Only the variable of
collectives (p = .02) was significantly higher in white-authored
messages. Definitions of these seven significant variables are provided in
Table 3. Commonality is one of Diction’s five Master Variables, calculated by
combining the variables of centrality, cooperation, and rapport, and
subtracting from this subtotal the variables of diversity, exclusion, and
liberation. Despite a clear black/white difference in commonality at the level
of p < .05, however, significant black/white differences were not
recorded in any of the six components of this Master Variable, suggesting a
small but consistent trend rather than a single spike within one of the six
components. Definitions of the six components of commonality are included in
Table 3.
Answering RQ2 in the negative, a
similar analysis of the 114 sets of comments appended to these blog posts found
no variables fluctuating significantly based on the race of the author of the
message on which readers were commenting. No effort was made to determine the
race of each commenter because of a clear trend of anonymity for such blog
comments.
Providing an answer to RQ3, about
incivility, requires a discussion of what it means that black authors reflected
higher levels of cognition, commonality, hardship, human interest,
satisfaction, and self-reference, as well as a lower level of collectives.
Discussion
Commonality: The higher mean
score for the Diction master variable of commonality for black-authored blog
posts than for white-authored ones is indicative of increased use of words that
express agreement on core values (centrality), working together as a group
(cooperation), and sharing attitudinal similarities as a group (rapport). It
also indicates decreased use of words that describe individuals who differ from
the group norm (diversity), social isolation (exclusion), and the importance of
individual freedom above social convention (liberation). Within the sample of
blog posts about the death of Michael Brown and subsequent events in Ferguson,
the highest commonality score was 55.39 for a black-authored Huffington Post
article outlining five ways for educators to teach students about Michael Brown
in the coming year (Emdin,
2014), and the top four scores for commonality were all for black-authored
messages. Among white-authored posts, the highest score for commonality was
52.45 for an assertion that widespread grassroots opposition to the
militarization of local police departments was unlikely to lead to bipartisan
legislation to stop it (Donovan,
2014). The high black commonality score can be seen as evidence of what
social identity predicts, that an online African-American community would
coalesce around the discussion of issues common to their experience.
Cognition: The heightened variable
of cognitive terms in the writings of black bloggers suggests that overall they
made greater use than white bloggers of words expressing both rationalistic
(perception, speculation, judging) and intuitional (knowledge, thinking,
inquiry) thought processes. The highest cognition score from a black-authored
post was 35.57 on the aforementioned article on how to teach students about
Michael Brown (Emdin, 2014). The second highest score was 23.97 on a brief
exhortation by MLK niece Dr. Alveda C. King on Newsmax.com to “think rationally,
honestly, and morally right to accord with the thinking of the creator” (King,
2014). The highest white-authored cognition score of 40.21 was on a Think
Progress explanation of why an aircraft “no-fly zone” had been imposed on Ferguson
(Strasser,
2014). The higher black score on this variable suggests assertions by
African-American authors that more attention needs to be focused on Ferguson,
with greater efforts made to understand events and their broader implications. Again,
this can be seen as consistent with SIT expectations of the emergence of a
black community coalescing via blog messages about how to deal with common
issues and implications.
Hardship: A higher mean
score for the variable of hardship within black-authored blog posts is
indicative of a variety of negative actions, from natural disasters
(starvation, tornado, pollution) to hostile (rebellion, bankruptcy, infidelity)
or even illegal human behavior (slavery, exploitation, killers). The highest
hardship score from a black-authored post was 22.35 for a Salon essay that drew
examples from a century of mistreatment by whites in defending black rage:
Nothing
makes white people more uncomfortable than black anger. But nothing is more
threatening to black people on a systemic level than white anger. It won’t show
up in mass killings. It will show up in over-policing, mass incarceration, the
gutting of the social safety net, and the occasional dead black kid. Of late,
though, these killings have been far more than occasional. We should sit up and
pay attention to where this trail of black bodies leads us. They are a compass
pointing us to a raging fire just beneath the surface of our national
consciousness. We feel it. We hear it. Our nostrils flare with the smell of it
(Cooper,
2014).
Scoring 17.67 for its hardship
tone, the next highest black-authored message was the aforementioned piece by
Alveda C. King, who also drew on historic examples from her uncle’s struggle
for civil rights in the 1960s to explain contemporary black rage (King, 2014).
The highest score for hardship in the entire sample was 29.66 for a brief,
white-authored pondering of how the events in Ferguson would have been covered
by news media if they happened in China or Russia (Byers,
2014). The higher black score on this variable suggests that black authors
more frequently tied events in Ferguson into a broader narrative of past and
present grievances shared by the community, again consistent with SIT
expectations.
Human-interest: The human-interest
variable attempts to measure the extent to which human beings and their
activities are central to the discourse. Its dictionary includes personal
pronouns, words describing family members and generic human terms. The highest
human-interest score was 70 for a Huffington Post “open letter to the people of
Ferguson” whose author referred to himself as an African-American male and
reflected on the pain felt by Michael Brown’s grandmother as well as by wider
categories of black mothers and fathers (Sanders,
2014). The highest white human-interest score was 68 for a vote of
confidence in the investigation of U.S. Attorney General Eric Holder, which
dealt with the autopsy performed on Michael Brown’s body (Salzillo,
2014). The higher black mean on this variable suggests that black authors
treated the subject from a more personal viewpoint, discussing its effects on
individual human beings or on specific groups of people. Once again, this can
be seen as consistent with the predictions of SIT.
Satisfaction: The variable
of satisfaction measures the presence of terms associated with joy, pleasure,
triumph and other positive affective states. A black-authored Huffington Post
essay praising the Internet for giving African-Americans a better way to rally
support and form communities earned the highest score for satisfaction, at
19.86 (Cyril,
2014). The highest satisfaction score for a white-authored post was 17.62
for the Salzillo (2014) essay mentioned above that compliments the
investigation by the U.S. attorney general. Again, the higher mean score for
black-authored messages is consistent with an SIT expectation that membership
in any in-group is likely to bring with it an optimized attitude about the
benefits of belonging to that group.
Self-reference: The variable
of self-reference indexes all first-person references—such as I, I’m, I’ve, me,
mine, myself—to show instances in which “the locus of action appears to reside
in the speaker and not in the world at large.” The top score for black-authored
self-reference is 27.28 on a mother’s first-person narrative that begins:
I
don’t want to talk about the boy and the sneakers peeking out from the sheet
crudely draped over his corpse in the street, because I have been happy this
month and it is so rare that I'm happy and that you, at age four, don’t have to
touch my knee or shoulder or face and say, “What's wrong, Mama? You sad?” (Brown,
2014)
The highest self-reference score
for a message by a white author is 36.25, again for the Salzillo attorney
general essay. Next behind that is a score of 16.87 for a point-by-point
analysis of events in Ferguson in which the author offers his personal
expertise on a number of topics, including concussions, police radio technology,
and the Trayvon Martin case (Hayden,
2014). Again, the higher black-authored mean for this variable is
consistent with SIT predictions that personal identity will be closely tied to
in-group membership.
Collectives: Only on the
variable of collectives was the mean score for black-authored messages
significantly lower than for white-authored ones. In a way, this variable can
be seen as the opposite of self-reference, in that it is built on terms that
describe groups in mostly non-specific ways, such as team, crowd, staff,
county, republic. A higher mean score for white-authored messages can be read
as the consequence of less personal involvement with the issue being discussed
than is exhibited by black bloggers. As in all of the six above variables
exhibiting a significant difference along racial lines, this finding appears to
be consistent with SIT expectations.
More study is needed to clarify the
processes by which online communities emerge and operate, especially in times
of crisis, but the present study does suggest that among black authors writing
about a news event of especially high salience for African-Americans, the ways
in which their messages had a different tone than those written by whites on
the same topic were consistent with qualities that social identity theory would
expect to see. It is just as important to note that these seven differences,
the only ones measured by Diction’s spectrum of variables, do not seem
consistent with heightened expressions of incivility. Certainly it is possible
that tones indicating hostility, anger, resentment, and even calls for violence
are heightened by either black or white bloggers, but if that is the case,
future researchers may need to employ different tools to measure it.
Table 1: ANOVAs of Diction variables that differ significantly by
bloggers’ race
Cognition:
Black-authored
posts are higher than white at the .05 level
Source Type III Sum df Mean F Sig. Partial
Eta
of
Squares Square Squared
Corrected Model 229.595b 1 229.595 6.682 .011 .041
Intercept 8017.873 1 8017.873 233.344 .000 .601
Author race 229.595 1 229.595 6.682 .011 .041
Error 5325.921 155 34.361
Total 14657.155 157
Corrected Total 5555.516 156
R Squared = .041 (Adjusted R Squared = .035)
Commonality:
Black-authored
posts are higher than white at the .05 level
Source Type III Sum df Mean F Sig. Partial
Eta
of
Squares Square Squared
Corrected Model 20.978b 1 20.978 5.211 .024 .033
Intercept 279071.871 1 279071.871 69327.730 .000 .998
Author race 20.978 1 20.978 5.211 .024 .033
Error 623.937 155 4.025
Total 377548.997 157
Corrected Total 644.915 156
R Squared = .033 (Adjusted R Squared = .026)
Hardship:
Black-authored
posts are higher than white at the .05 level
Source Type III Sum df Mean F Sig. Partial
Eta
of
Squares Square Squared
Corrected Model 127.440b 1 127.440 5.660 .019 .035
Intercept 7839.688 1 7839.688 348.197 .000 .692
Author race 127.440 1 127.440 5.660 .019 .035
Error 3489.843 155 22.515
Total 12941.373 157
Corrected Total 3617.283 156
R Squared = .035 (Adjusted R Squared = .029)
Human
Interest: Black-authored posts are higher than white at the .005 level
Source Type III Sum df Mean F Sig. Partial
Eta
of
Squares Square Squared
Corrected Model 1287.043b 1 1287.043 10.370 .002 .063
Intercept 67712.709 1 67712.709 545.596 .000 .779
Author race 1287.043 1 1287.043 10.370 .002 .063
Error 19236.709 155 124.108
Total 100137.807 157
Corrected Total 20523.752 156
R Squared = .063 (Adjusted R Squared = .057)
Satisfaction:
Black-authored
posts are higher than white at the .05 level
Source Type III Sum df Mean F Sig. Partial
Eta
of
Squares Square Squared
Corrected Model 43.307b 1 43.307 4.715 .031 .030
Intercept 1344.893 1 1344.893 146.427 .000 .486
Author race 43.307 1 43.307 4.715 .031 .030
Error 1423.637 155 9.185
Total 2976.025 157
Corrected Total 1466.944 156
R Squared = .030 (Adjusted R Squared = .023)
Self-reference:
Black-authored
posts are higher than white at the .005 level
Source Type III Sum df Mean F Sig. Partial
Eta
of
Squares Square Squared
Corrected Model 253.025b 1 253.025 11.505 .001 .069
Intercept 1517.574 1 1517.574 69.003 .000 .308
Author race 253.025 1 253.025 11.505 .001 .069
Error 3408.916 155 21.993
Total 4950.432 157
Corrected Total 3661.941 156
R Squared = .069 (Adjusted R Squared = .063)
Collectives: White-authored posts are higher than black at the .05 level
Source Type III Sum df Mean F Sig. Partial
Eta
of
Squares Square Squared
Corrected Model 189.028b 1 189.028 5.098 .025 .032
Intercept 12662.760 1 12662.760 341.498 .000 .688
Author race 189.028 1 189.028 5.098 .025 .032
Error 5747.398 155 37.080
Total 25436.331 157
Corrected Total 5936.426 156
R Squared = .032 (Adjusted R Squared = .026)
Table 2: Descriptives of Diction variables that differ
significantly by blogger race
N Mean Std.
Dev. Std. Error Lower Upper Min. Max.
White 119 6.930588 5.5283777 .5067856 5.927015 7.934162 .0000 40.2100
Black 38 9.753947 6.8170920 1.1058784 7.513225 11.994670 1.2300 35.5700
Total 157 7.613949 5.9676028 .4762666 6.673186 8.554712 .0000 40.2100
White 119 48.7900 1.90391 .17453 48.4444 49.1356 41.86 52.45
Black 38 49.6434 2.30278 .37356 48.8865 50.4003 44.92 55.39
Total 157 48.9966 2.03324 .16227 48.6760 49.3171 41.86 55.39
White 119 7.197311 4.7466293 .4351228 6.335649 8.058973 .0000 29.6600
Black 38 9.300789 4.7398394 .7689035 7.742843 10.858736 .5000 22.3500
Total 157 7.706433 4.8153620 .3843077 6.947315 8.465551 .0000 29.6600
White 119 20.900840 10.6559219 .9768268 18.966457 22.835223 1.7600 68.0000
Black 38 27.585526 12.5611653 2.0376901 23.456774 31.714279 8.9000 70.0000
Total 157 22.518790 11.4700703 .9154113 20.710589 24.326990 1.7600 70.0000
White 119 2.803529 2.5626293 .2349158 2.338332 3.268727 .0000 17.6200
Black 38 4.029737 4.1872499 .6792616 2.653422 5.406052 .0000 19.8600
Total 157 3.100318 3.0665111 .2447342 2.616898 3.583739 .0000 19.8600
White 119 2.147395 4.2646838 .3909429 1.373222 2.921568 .0000 36.2500
Black 38 5.111316 5.8420369 .9477035 3.191086 7.031546 .0000 27.2800
Total 157 2.864777 4.8449956 .3866727 2.100987 3.628567 .0000 36.2500
White 119 11.764706 6.2408577 .5720985 10.631795 12.897617 2.5400 30.0800
Black 38 9.202895 5.5786712 .9049800 7.369231 11.036558 1.3200 22.7700
Total 157 11.144650 6.1687933 .4923233 10.172170 12.117130 1.3200 30.0800
Table
3: Definitions of the 7 Diction variables found to be significant
Cognitive
terms:Words
referring to cerebral processes, both functional and imaginative. Included are modes of discovery (learn, deliberate,
consider, compare)
and domains of study (biology,
psychology, logic, economics). The dictionary includes mental challenges
(question, forget, re-examine, paradoxes), institutional learning practices (graduation,
teaching, classrooms),
as well as three forms of intellection: intuitional (invent, perceive, speculate, interpret), rationalistic (estimate, examine,
reasonable, strategies),
and calculative (diagnose, analyze,
software, fact-finding).
Commonality
(1
of 5 Diction master variables): Language highlighting the agreed-upon
values of a group and rejecting idiosyncratic modes of engagement. Commonality
Formula built by converting these variables to Z-scores, then concatenating
them as: [Centrality + Cooperation + Rapport] – [Diversity + Exclusion +
Liberation]. These six components are defined as:
CENTRALITY: Terms denoting
institutional regularities and/or substantive agreement on core values.
Included are indigenous terms (native, basic, innate) and designations of legitimacy (orthodox, decorum,
constitutional, ratified),
systematicity (paradigm,
bureaucratic, ritualistic),
and typicality (standardized,
matter-of-fact, regularity).
Also included are terms of congruence (conformity, mandate, unanimous),
predictability (expected, continuity, reliable), and universality (womankind,
perennial, landmarks).
COOPERATION: Terms designating
behavioral interactions among people that often result in a group product.
Included are designations of formal work relations (unions, schoolmates,
caucus)
and informal associations (chum, partner, cronies) to more intimate interactions (sisterhood,
friendship, comrade).
Also included are neutral interactions (consolidate, mediate, alignment), job-related tasks
(network,
detente, exchange),
personal involvement (teamwork,
sharing, contribute),
and self-denial (public-
spirited, care-taking, self-sacrifice).
RAPPORT: This dictionary
describes attitudinal similarities among groups of people. Included are terms
of affinity (congenial,
camaraderie, companion),
assent (approve,
vouched, warrants),
deference (tolerant,
willing, permission),
and id entity (equivalent,
resemble, consensus).
DIVERSITY: Words describing
individuals or groups of individuals differing from the norm. Such
distinctiveness may be comparatively neutral (inconsistent, contrasting,
non-conformist)
but it can also be positive (exceptional, unique, individualistic) and negative (illegitimate,
rabble-rouser, extremist).
Functionally, heterogeneity may be an asset (far-flung, dispersed, diffuse) or a liability (factionalism, deviancy,
quirky)
as can its characterizations: rare vs. queer, variety
vs. jumble, distinctive vs. disobedient.
EXCLUSION: A dictionary
describing the sources and effects of social isolation. Such seclusion can be
phrased passively (displaced,
sequestered)
as well as positively (self-contained,
self-sufficient)
and negatively (outlaws,
repudiated).
Moreover, it can result from voluntary forces (secede, privacy) and involuntary
forces (ostracize,
forsake, discriminate)
and from both personality factors (smallmindedness, loneliness) and political
factors (right-wingers,
nihilism).
Exclusion is often a dialectical concept: hermit vs. derelict, refugee vs. pariah, discard vs. spurn).
LIBERATION: Terms describing the
maximizing of individual choice (autonomous, open-minded, options) and the rejection
of social conventions (unencumbered,
radical, released).
Liberation is motivated by both personality factors (eccentric, impetuous, flighty) and political
forces (suffrage,
liberty, freedom, emancipation) and may produce dramatic outcomes (exodus, riotous,
deliverance)
or subdued effects (loosen,
disentangle,
outpouring). Liberatory terms
also admit to rival characterizations: exemption vs. loophole, elope vs. abscond, uninhibited
vs. outlandish.
Hardship: This dictionary
contains natural
disasters (earthquake,
starvation, tornado, pollution), hostile actions (killers, bankruptcy, enemies, vices) and censurable human
behavior (infidelity,
despots, betrayal).
It also includes unsavory
political outcomes (injustice, slavery,
exploitation, rebellion)
as well as normal
human fears (grief,
unemployment, died, apprehension) and incapacities (error, cop-outs, weakness).
Human
interest:
An
adaptation of Rudolf Flesch’s notion that concentrating on people and their
activities gives discourse a life-like quality. Included are standard personal
pronouns (he,
his, ourselves,
them), family members and relations (cousin, wife, grandchild, uncle), and
generic terms (friend, baby, human, persons).
Satisfaction: Terms associated
with positive
affective states (cheerful,
passionate, happiness),
with moments of undiminished
joy (thanks, smile,
welcome)
and pleasurable
diversion (excited, fun,
lucky), or
with moments
of triumph (celebrating, pride,
auspicious). Also
included are words
of nurturance:
healing,
encourage, secure, relieved.
Self-reference: All first-person
references,
including I,
I’d, I’ll, I’m, I’ve, me, mine, my, myself. Self- references are treated as acts of
indexing whereby the locus of action appears to reside in the speaker and not
in the world at large thereby implicitly acknowledging the speaker’s limited
vision.
Collectives: Singular nouns
connoting plurality that function to decrease specificity. These words reflect
a dependence on categorical modes of thought. Included are social groupings (crowd, choir, team,
humanity),
task
groups (army, congress,
legislature, staff)
and geographical
entities (county, world,
kingdom, republic).
Author Bio
Doug Mendenhall is an assistant professor in the Department of Journalism and Mass Communication at Abilene Christian University, where he is journalist in residence, teaches courses related to writing, history, race and religion, and oversees the department’s internship program. In 2013 he was instrumental in developing the department’s guest lecture series on race and media.
Mendenhall joined the ACU faculty in 2008 after a 26-year career with daily newspapers in Texas, Tennessee and Alabama, with an emphasis on design and graphics. Since 2000 he has written a weekly newspaper column on matters of faith and values.
Mendenhall earned his master’s degree from Middle Tennessee State University in 2003, with a dissertation that used live newspaper distribution to compare the audience’s perceptions of two different design styles on a single front page. He earned his doctorate in 2014 from Texas Tech University with a dissertation titled, “Comparing Levels of Incivility Across Political and Religious Blog Posts.”
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