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Abstract
Governments increasingly turn to the Internet to aid in transparency, accountability, and public participation activities, and there is growing interest in innovative online problem-solving models to serve the public good. One such model, the crowdsourcing model, leverages the collective intelligence of online communities for specific purposes. Understanding how and why people participate in these kinds of activities is important for developing better new media tools for the public good going forward. In 2009, the Federal Transit Administration supported the Next Stop Design project, an attempt to use crowdsourcing for public participation in transit planning. Based on interviews with 23 Next Stop Design participants, the present applied communication study discusses the motivations of those participants to engage the project.
Notes
1. The 23 interviews were conducted on the following instant messenger programs per the participant's choosing: Google Talk (9), MSN Live Messenger (7), Skype text-only chat (3), Yahoo! Messenger (2), iChat (1), AOL Instant Messenger (1).
2. Transcript excerpts are presented in this paper as true as possible to the expressive capabilities available to participants (including capitalization); the limitations of mediated synchronous communication; and the limitations of the specific IM program used for interviewing. There are many grammatical, spelling, punctuation, and capitalization errors present in the transcript excerpts, and these have been maintained to remain true to the participants’ words. Each discrete message is displayed in its own line of text. The use of brackets in the manuscript indicates either unimportant commentary omitted by the author or the participant's intended edits that I compiled for ease of reading. In the latter case, for example, if a participant types “shortwhiel” in one line, but immediately follows it up with “short while” in another message, it is understood that the participant intended to correct his or her spelling error in the previous message, per the norms of IM conversations. In a case such as this, “[short while]” is included in place of the initial instance of misspelling. In other words, interview transcript excerpts are mostly unedited in terms of mechanics and style, and they contain many mechanical errors that were present in the raw transcripts.