David Lazer

Expanding the Conversation: Multiplier Effects From a Deliberative Field Experiment

Do formal deliberative events influence larger patterns of political discussion and public opinion? Critics argue that only a tiny number of people can participate in any given gathering and that deliberation may not remedy—and may in fact exacerbate—inequalities. We assess these criticisms with an experimental design merging a formal deliberative session with data on participants’ social networks. We conducted a field experiment in which randomly selected constituents attended an online deliberative session with their U.S. Senator. We find that attending the deliberative session dramatically increased interpersonal political discussion on topics relating to the event. Importantly, after an extensive series of moderation checks, we find that no participant/nodal characteristics, or dyadic/network characteristics, conditioned these effects; this provides reassurance that observed, positive spillovers are not limited to certain portions of the citizenry. The results of our study suggest that even relatively small-scale deliberative encounters can have a broader effect in the mass public, and that these events are equal-opportunity multipliers.

Evaluation of the First US PhD Program in Network Science: Developing Twenty-First-Century Thinkers to Meet the Challenges of a Globalized Society

With this chapter, we present Northeastern University’s doctoral program in network science. The program began in 2014, representing the first (and currently the only) PhD program in network science in the United States. We present the vision for the program, an overview of the curriculum, the supervision and advisor process, and an evaluation of the program. We describe adjustments and revisions that we have implemented and provide a more holistic vision for how we anticipate the program will contribute to society. The chapter is structured as follows: (a) discussion of the purpose of our PhD program in network science (section 1), (b) description of the objectives and curriculum of the PhD program (sections 2, 3 and 4), and (c) evaluation of the program, discussion of the changes we have already introduced and strategies for further addressing the needs of the growing workforce in data and computational sciences (section 5). The hope is that documenting the process of curriculum development, particularly in interdisciplinary STEM fields, will both inspire new initiatives and provide a framework for growing new educational programs.