This paper studies how a large online community made sense of a television and online news organization's cosponsored study of children's perceptions of race in the America. 2,906 readers' comments from the CNN special report were collected in December 2010. After classifying these comments, there were four data sets: all comments, negative comments, positive comments, and popular comments (comments with "Like). Wordstat, a contentanalysis software program, was used to analyze the word/phrase frequency of four data sets. The purpose of the content analysis was to identify any similar pattern of word/phrase among the data sets. Of 2,906 comments, 1,745 comments (60%) received the "Like" votes from other online readers. However, the majority of these comments (1,723; 59.29%) received fewer than 26 votes of "Like." Regarding the positive comments, only 68 comments were agreed upon by the three reviewers. Seven of those comments were highly positive (over 6 based on a 7-point Likert scale). On the other side, 456 comments were agreed upon by the reviewers as negative comments. However, the majority of those comments (443) were slightly negative (2.01-3 based on a 7-point Likert scale).