Introduction

1. Introduction Librarians who provide instant message-based (IM) virtual reference services often perceive that their patrons self-identify to some degree, even when transactions are anonymous. Over time, they begin to form conclusions about their patrons’ characteristics as a group. Sobel and Roper decided to investigate the realities behind these perceptions. They analyzed two years’ worth of IM reference transcripts to see what demographic information their patrons really provided. This work resulted in two major products: • Detailed and concrete information about their IM reference users’ characteristics • A method for analyzing transcripts to identify demographics of patron groups over time The researchers believe that other libraries will benefit from using the methodology they have developed to investigate their users’ demographics through identifiers provided during individual conversations. Methodology The following methodology can be easily adapted to assess patron group demographics at any library. While Sobel and Roper performed their research at an academic library, public and other libraries providing IM reference service can investigate the patron characteristics that matter most to their work. • The researchers selected representative time periods to study (Fall semester 2009 and Fall semester 2010). • The researchers created a random sample scheme for selecting transcripts to study. They chose to do this by identifying peak times of service: 10AM-noon and 2PM-4PM. They then selected the transcript closest to the middle of each of these time periods every day. This created the group of samples from which they drew their conclusions. • The researchers identified the demographic characteristics most affecting individual reference transactions at their institution. Most reflected demographics; some data on academic needs was also gathered. Choices were based on their personal expertise and judgment. Characteristics selected were:origin of message (for example, through a chat box embedded on a course page), gender, age group, school (the library serves three institutions of higher education), full-time or part-time enrollment, year in school, and English as a Second Language status. Information on academic needs included the subject area of the question (when applicable), and major category of reference need (such as assistance with a database or basic library information). • The researchers wrote detailed criteria for evaluating each characteristic. For example, transcripts identified as coming from a speaker of English as a Second Language might include an explicit explanation “Hi, I am an international student from Japan and I need help with….” It might also include language or spellings pointing to other languages (such as “jaja” instead of “haha,” or syntax pointing to non-native speech. • Roper carefully reviewed all the selected transcripts and reviewed each characteristic for every transcript. • The researchers compiled the data in a spreadsheet using Microsoft Excel. They had decided prior to performing the study that they were most interested in raw numbers and simple frequencies. (More robust statistical software such as R or SPSS could calculate correlations or evaluate statistical validity for libraries interested in exploring these factors.)