Extracting author-specifi c expressions using random forest for use in the sociolinguistic analysis of political speeches

This study applies stylistic text classifi cation using random forest to extract author-specifi c expressions for use in the sociolinguistic analysis of political speeches. In the fi eld of politics, the style of political leaders’ speeches, as well as their content, has attracted growing attention in both English (Ahren, 2005) and Japanese (Azuma, 2006; Suzuki and Kageura, 2006). One of the main purposes of these studies is to investigate political leaders’ individual and political styles by analyzing their speech styles. A common problem of many of these studies and also many sociolinguistic studies is that the expressions that are analyzed are selected solely on the basis of the researcher’s interests or preferences, which can sometimes lead to contradictory interpretations. In other words, it is diffi cult to determine whether these kind of analyses have in fact correctly identifi ed political leaders’ individual speech styles and, on this basis, correctly characterised their individual and political styles. Another problem is that political leaders’ speech styles may also be characterised by the infrequent use of specifi c expressions, but this is rarely focused on.