Analyzing Sentiments from Street Harassment Stories
Advisor Information
Parvathi Chundi
Location
Milo Bail Student Center Council Room
Presentation Type
Oral Presentation
Start Date
8-3-2013 10:00 AM
End Date
8-3-2013 10:15 AM
Abstract
Street harassment is a pervasive problem that typically targets women and LGBTQ community. There are currently no effective methods to deal with the harassers because the acts of harassment happen randomly and are difficult, if not impossible, to prosecute. Hollaback! is an international movement aimed at stopping street harassment, and one of the ways Hollaback! raises awareness and gathers statistics is through supporting a system of blog posts through which Hollaback! servers collect street harassment stories from victims around the globe. In this research, we completed a preliminary study focused on analyzing small samples of Hollaback! stories submitted from major cities such as New York city. The LIWC software we employ is used to measure the positive and negative emotions hidden in each story and correlate it to the socioeconomic status of the location from which the story was submitted, which is validated through pronoun function rates already identified with socioeconomic status [2]. This research creates a localized knowledge of street harassment effects.
Analyzing Sentiments from Street Harassment Stories
Milo Bail Student Center Council Room
Street harassment is a pervasive problem that typically targets women and LGBTQ community. There are currently no effective methods to deal with the harassers because the acts of harassment happen randomly and are difficult, if not impossible, to prosecute. Hollaback! is an international movement aimed at stopping street harassment, and one of the ways Hollaback! raises awareness and gathers statistics is through supporting a system of blog posts through which Hollaback! servers collect street harassment stories from victims around the globe. In this research, we completed a preliminary study focused on analyzing small samples of Hollaback! stories submitted from major cities such as New York city. The LIWC software we employ is used to measure the positive and negative emotions hidden in each story and correlate it to the socioeconomic status of the location from which the story was submitted, which is validated through pronoun function rates already identified with socioeconomic status [2]. This research creates a localized knowledge of street harassment effects.