A Semantic Network Analysis of The Network Neutrality Debate

Abstract

With nearly 4 million remarks, the 2014 proceeding that produced the recently released Open Internet Order stands as the most commented Federal Communications Commission (FCC) docket to date. According to FCC Chair Tom Wheeler, the volume and substance of this public input was crucial in shifting the agency’s final rules away from legal justifications based on Section 706 towards Title II reclassification. Mass public sentiment had a significant impact on agency decision-making. The bulk release of comments thus gives communication researchers an opportunity to more fully understand the formation and expression of public opinion. Using a variety of proven data mining and semantic network analysis techniques, this paper will conduct an exploratory but comprehensive quantitative inquiry of the comments.Previous quantitative surveys have been enveloped in controversy. In particular, the Sunlight Foundation’s analysis sparked a number of responses and counter analyses by involved think tanks and activists, requiring further clarification by the organization and an official response by the FCC. By first reproducing and then extending this work, this paper will serve as a first step in establishing an official understanding of the public’s input.This paper is divided into four sections. The first section provides a literature review of the relevant research from both psychology and communication theory that undergirds semantic network analysis. The second section seeks to answer a number of key questions that still remain after the initial round of research. For example, how many comments mentioned and then supported Title II reclassification? Of the total submitted comments, how many were due to form submissions? From which organizations did these form submissions come? How many of the comments were not related to network neutrality but still expressed general concern with the state of the American broadband industry? Moreover, just how many of the comments were not related to any broadband concern?The third will employ a variety of data mining techniques including word-pair link strength and k-nearest neighbors algorithms to chart changes in semantic networks as a quantitative proxy for changing public opinion. By parsing comments into a number of time series, changes between the two sets can be tracked. Four time sets have been identified. The first will compare comments during the first and last 30 days of the official comment period. The second time series will explore the influence of popular television host John Oliver. His widely shared and viewed TV segment ended with a call for viewers to file comments in the proceeding that immediately crashed the FCC comment system. By comparing those comments filed 30 days after and 30 days before the show ran, a measure of his influence on the conversation will be established. Next, the importance of Internet Slowdown Day, an event popularized by a number of activist groups will undergo analysis through a similar 30 day before and after comparison. Lastly, all of the comments in the initial round of comments will be compared to those of the reply round. The fourth and final section will review conclusions from the research and outline opportunities for future studies.