This study began with a goal of investigating self-identifying practices and salient identities in otherwise anonymous posts. This is a mixed-method approach, providing quantitative data (corollary, and regressional) about system-level identity variables (i.e., age, gender, sexual orientation, etc.), and qualitative findings (via digital ethnography) about intra-post identity information included the post’s main content. Ethnographic work was performed on a randomly selected subset of the total dataset (N=300).
Data Collection
The dataset (N=2518) was obtained via a custom software application written by the author to collect posts from craigslist Missed Connections, and monitor if and when posts were censored. This dataset represents a random selection of censored (N=582) and uncensored (N=1936) posts submitted to craigslist Missed Connections in Washington D.C., New York City, and the San Francisco Bay Area. All posts were submitted between November 1st and the 30th, 2008; censored posts that were censored after this timeframe were excluded from this study.
The mean age of authors, when reported, was 31.45 (SD=10.95). Posts were collected from the four gender/sexual orientation subsections of Missed Connections: m4m (N=497, 19.7%), m4w (N=920, 36.5%), w4m (N=560, 22.2%), w4w (N=95, 3.8%).
SPAM. Posts considered SPAM were omitted from this study (N=520). The original working dataset for this study consisted of 3038 posts. Upon examining the posts, however, censored content appeared to predominantly consist of SPAM. In order to prevent erroneous finding, I coded each post based on whether I believed it counted as SPAM. The coding system used was designed to remove content that was potentially submitted by an automated system, while preserving posts appearing to have submitted by an actual individual. Because the true source of the post is unknown, a post was marked as SPAM if it was: viral, appearing frequently and across multiple channels; commercially soliciting the reader; linked to another website (most often craigslist competitors).