Zeynep Aslan
This report analyses the last statements of Texas death row inmates. Specifically, this report examines the last words of the inmates to reveal the common topics underlying their statements and to explore overall emotional tone of these statements. The report also includes specific analyses looking at the relationship between the inmates’ last statements and their demographic information, such as race and age.
Before getting into more detailed analyses, let’s check first the most frequent words used by the inmates in their last statements.
The word cloud in Figure 1 demonstrates 100 most frequent words used by the Texas death row inmates in their last statements. Darker colors and bigger fonts suggest higher frequency. Looking at the graph, we can see that the word “Love” appears most frequently in the last statements of inmates.
Similar to Figure 1, Figure 2 shows the most frequent 10 words used in the last statements of Texas death row inmates. Even from this preliminary analysis, we can observe some clear patterns: Most inmates use their last statements as a chance to express their love for their families and friends and seek forgiveness for their crimes by turning to religion.
Now, let’s apply topic modeling to the data to uncover the potential themes underlying the last statements of the inmates.
Figure 3 shows 6 potential topics underlying the last statements of the death row inmates. All 6 topics look pretty much the same, there are no clear patterns that can differentiate the topics from each other. 5 out of 6 topics include the word love (topics 1, 2, 4, 5, and 6) and half of the topics reveal the remorse of the inmate with the words sorry and forgive (topics 2, 3, and 6). Some of the topics also include religious references such as words holy and god (topics 3 and 6). It is important to note that the topics does not become any more distinguishable/interpretable by increasing or decreasing the number of models specified in model structure.
In this part of the report, we will analyze whether or not we can estimate the races of inmates depending on their last statements. Before running a predictive model to test this question, let’s check the most frequent words used by inmates of each race.
Figure 4 demonstrates the most frequent words used by inmates of different races in their last statements. When we compare the graphs, we can see that there is a great deal of consistency between race groups in terms of the themes of the last statements: As also shown in Figure 1 and 2, inmates of all races express their love for their families and ask for forgiveness from the God in their last statements.
Now, let’s estimate a random forest model with 10-folds cross-validation to test if we can predict the race of an inmate based purely on their last statements.
| Metric | Estimator | Mean | n | Standard Error |
|---|---|---|---|---|
| accuracy | multiclass | 0.34 | 10 | 0.02 |
Table 1 shows the performance of the model. The average accuracy of the model was 34%, which is not great at all. Confusion matrix also displays the sub-optimal performance of the model. We can see that the model most accurately predicts the races of White individuals but even that performance is very bad. Overall, the results of the predictive model suggests that the last statements of inmates do not carry much informative value about the races of their speakers.
Finally, let’s estimate the sentiment of the last statements of the death row inmates.
Figure 6 demonstrates the top 10 most frequently used positive and negative words in the last statements of the death row inmates. The last statements of the inmates generally have a positive rather than negative tone. This is interesting and quite tragic, considering that these words were uttered by people who were in the last few minutes of their lives. However, when positive words are examined more closely, it can be understood where this positivity stems from: It seems like inmates made peace with the fact that their lives were about to end and they were ready to pass to the ‘other side’. On another note, the word love outweighs in the last statements of inmates (i.e., more than half of the inmates who made a statement articulated the word love in their statements) and this is because inmates also use their last statements to express their love for their families who were there for their execution.
Lastly, Figure 7 demonstrates the relationship between the ages of the inmates at the time of their execution and the sentiment level of their last statements. The sentiment level of each word in a last statement is coded using the AFINN dataset. AFINN is a lexicon of English words rated for valence with a range between -5 (negative) to 5 (positive). As can be seen from Figure 1, across all ages, the last statements of the inmates are slightly positive. However, there seems to be no relationship between inmates’ ages and the sentiment level of their last statements.