the narrative strategies that the blogs of hate groups adopted before and after a central political event, namely, the 2008 election of President Obama in the U.S. Using data from a large number of hate blogs (N=600), and sentiment analysis and data mining, we tested two alternative hypotheses derived from social identification theory. We found that there were major differences between the content of these blogs before the election and immediately after the 2008 election, with the latter evincing an increase in the advocacy of violence and hostility. We also determined that faced with this new change, the hate groups adopted a social competition strategy rather than a creativity strategy to manage their identity. Our findings imply that since the election of Barack Obama as President, the worldview of online hate groups has become more violent.The authors comment that
The purpose of this study was to examine the narrative strategies used by hate groups that are active in the blogosphere. For this study, we collected data on racial attitudes expressed in a large number of blogs at two points in time: before the 2008 election and immediately after the election. Using the innovative techniques of sentiment analysis, we determined the distribution of words used to express positive and negative emotions and behaviors about racial and ethnic relations as expressed in the blogs of hate groups. Our study design allowed us to investigate changes in these expressions over time. Our first aim was to investigate whether the emotions expressed in the blogosphere changed as a result of the election of an African American President. According to the exemplars exposure hypothesis, exposure of an in–group to the positive image of a member of the stigmatized out–group may lead the former to develop a more positive view of the latter (Bodenhausen and Macrae, 1998; Welch and Sigelman, 2011). Our study showed no support for this argument. Indeed, immediately after the election, we found a moderate increase in the frequency of words appearing in the hate blogs denoting negative emotions and even negative behaviors. After the election, the content included concepts associated with and advocating violence and negative behavior.
After observing this change in negative emotions, we relied on social identification theory to determine whether in the face of the change in society that the election results implied, the blogs adopted a social competition strategy or a social creativity strategy to manage their identity. We showed that the characteristics of the textual context of hate blogs after the election were similar to the description of the social competition strategy that appears in the literature (Douglas, et al., 2005; Haslam, 2001; Tajfel and Turner, 1979). While we found evidence for both social competition and social creativity (evident in the examples we presented), the appearance of the concepts that called for hostility and advocated violence after the election is clear evidence of the preference for the social competition strategy. Scholars theorize that in–groups who have suffered a social change may adopt this strategy, which leads to the exacerbation of the relationship between in–groups and out–groups.
xxx It is important to note that our findings differ slightly from those of a previous study that investigated the competition strategy among 43 white supremacist Web sites and found minimal levels of the advocacy of violence (Douglas, et al., 2005). The difference between our results and those in that study might result from differences in sample size and the dimension of time. Douglas and colleagues studied only a few Web sites, while we included text from a large sample of bloggers. In addition, our study examined blogs at different points in time, so we were able to trace changes over time. In fact, the issue of time seems to be particularly relevant, given that the post–election expressions are significantly different from the political atmosphere before the election.
Our study has several limitations. First, it covers only the blogosphere. However, hate groups use other platforms as well such as Web sites, and textual and multimedia social network sites. Given that the detection of hate groups and the analysis of the user generated content in other platforms require different tools, it is difficult to generalize our findings to other platforms. Nevertheless, we suspect that such techniques might lead to even stronger support for our results.
Another limitation of this study relates to the fact that we relied on commercial tools (IBM–SPSS Text Mining and Data Mining technology). One of the common limitations of commercial technology lies in the fact that their algorithms are proprietary, making it difficult to understand how the machine obtained certain results, particularly when comparing the machine’s results with human judgment. Nevertheless, in practice, our study presents an innovative framework and methodology for the domain of behavioral studies. The main contribution of this research is the ability to detect the type of identity management strategy that hate groups adopt based on the textual content of their blogs. In the future, we look forward to comparative studies on other Web–based content sources. It should be interesting to see if we can apply our system to other online sources besides blogs.