Publication Type: Conference Paper/Unpublished Manuscript
Abstract: This paper explores the widespread practice of “beeping” between mobile phone users in sub-Saharan Africa. Beeping involves calling a number and hanging up before the mobile’s owner can pick up the call. The mobile’s call log and address book functions signal who called, and when. Most beeps are requests to the mobile owner to call back immediately, but beeps can also send a pre-negotiated instrumental message such as “pick me up now”, or send a relational sign, such as “I’m thinking of you”. Based on interviews with small business owners and university students in Rwanda, the paper identifies the “rules of beeping” and assesses its significance using a variety of frames, including linguistics, structuration, and communication technology and economic development. The paper contrasts beeping with SMS/text messaging, and suggests paths for future research.

Publication Type: Conference Paper/Unpublished Manuscript
Review Method: Peer Reviewed
Abstract: In the 2002 general election a field experiment was conducted in San Francisco. 5% of the call list for a GOTV mobilization drive was segregated into a control group; the rest were called as planned. Following the election, a comparison of the treatment and control groups revealed that the GOTV calls had virtually no effect on voter turnout. However, not everyone in the treatment group actually received the treatment – i.e., answering the telephone and listening to the message. Looking at only successfully completed calls, there was an apparent large effect, because these people voted at much higher rates than either the control group or members of the treatment group who did not receive the call. This is, of course, a selection effect – it is why we randomize. People who are available and willing to receive a GOTV call are different from people who are either not available or not willing. Indeed, there are even differences among those people who did not receive the call. I have data on the disposition of each call. While people who were successfully contacted voted at the highest rates, this is not the only distinction. The unwilling people vote at the next highest rate – people who answered the phone but hung up on the caller. Other distinctions exist as well. Among people who apparently were not home, people who had answering machines voted at higher rates than people who did not. This would be unsurprising if the callers left messages, but in fact they did not. There was also a very large distinction between wrong numbers and disconnected lines. This paper provides these data and explains some of the underlying theoretical reasons for these distinctions. It explains what the selection effect is, why it exists, and how experimental controls deal with it. It also discusses the methodological reasoning for analyzing data from both a random and non-random perspective to maximally leverage the information at one’s disposal.