COP TOPICS: TOPIC MODELING-ASSISTED DISCOVERIES OF POLICE-RELATED THEMES IN AFRICAN-AMERICAN JOURNALISTIC TEXTS

Abstract

The analysis of mainstream newspaper content has long been mined by communication scholars and researchers for insights into public opinion and perceptions. In recent years, scholars have been examining African-American authored periodicals to obtain similar insights. Hearkening back to the 1950s and 1960s civil rights movement in the United States, the highly-publicized killings of African-American men by police officers during the past several years have highlighted longstanding strained police-community relations. As part of its role as both a reflection of, and an advocate for, the African-American community, African-American journalistic texts contain a wealth of data about African-American public opinion about, and perceptions of, police. In years past, media content analysts would manually sift through newspapers to divine interesting police-related themes and variables worthy of study. But, with the exponential growth of digitized texts, communication scholars are experimenting with computerized text analysis tools like topic modeling software to aid them in their content analyses. This thesis considers to what degree topic modeling software can be used at the exploratory stage of designing a content analysis study to aid in uncovering themes and variables worthy of further investigation. Appendix A contains results of the manual exploratory content analysis. The list of topics generated by the topic modeling software may be found in Appendix B.