Reading data into R for ConversationAlign

Half the battle with R is getting your data imported and formatted. This is especially true for string data and working with text. ConversationAlign uses a series of sequential functions to import, clean, and format your raw data. You MUST run each of these functions. They append important variable names and automatically reshape your data.

Prepping your data for import

• ConversationAlign works ONLY on dyadic (i.e., two person) conversation transcripts.
• Each transcript must nominally contain two colummns, one column should delineate the interlocutor (person who produced the text), and another column should contain the text itself.
• ConversationAlign contains an import function called read_dyads() that will scan a target folder for text samples.
• read_dyads() will import all of your transcripts into R and concatenate them into a single dataframe.
• read_dyads() will append each transcript’s filename as a unique identifier for that conversation. This is SUPER important to remember when analyzing your data.
• Store each of your individual conversation transcripts (.csv, .txt, .ai) that you wish to concatenate into a corpus in a folder. ConversationAlign will search for a folder called my_transcripts in the same directory as your script. However, feel free to name your folder anything you like. You can specify a custom path as an argument to read_dyads()
• Each transcript must nominally contain two columns of data (Participant and Text). All other columns (e.g., meta-data) will be retained.

#will search for folder 'my_transcripts' in your current directory
MyConvos <- read_dyads()

#will scan custom folder called 'MyStuff' in your current directory, concatenating all files in that folder into a single dataframe
MyConvos2 <- read_dyads(my_path='/MyStuff')

MaryLittleLamb <- read_1file(MaronGross_2013)
#print first ten rows of header
knitr::kable(head(MaronGross_2013, 15), format = "pipe")