In this study I take a demographic perspective, analyzing age and mortality of books and articles which are cited, the authors that receive citations, and the authors writing the citations in the full published volumes of 73 sociology journals. I give a new operationalization of dates of deathβ for cited authors and cited works, as well as dates of rebirthα and document risk of death0.1 across the life course for cited works, cited authors, and writing authors in these journals. I report the top 1% cited works and cited authors, and on their untimely deaths. I discuss why sociologists should study sociology’s past and provide a Python package knowknow for replication and extension of these findings.

A person’s egonet, the set of others with whom that person is connected, is a personal sample of society which especially influences that person’s experience and perceptions of society. We show that egonets systematically misrepresent the general population because each person is included in as many egonets as that person has “friends.” Previous research has recognized that this unequal weighting in egonets leads many people to find that their friends have more friends than they themselves have. This paper builds upon that research to show that people’s egonets provide them with systematically biased samples of the population more generally. We discuss how this ubiquitous egonet bias may have far reaching implications for people’s experiences and perceptions of frequencies of other people’s ties and traits in ways that may influence their own feelings and behaviors. In particular, these egonet biases may help explain people’s tendencies to disproportionately experience and overestimate the prevalence of certain types of deviance and other social behaviors and consequently be influenced toward them. We illustrate egonet bias with analyses of all friends among 63,731 Facebook users. We call for further empirical investigation of egonet biases and their consequences for individuals and society.

This is a motivational essay for myself. My aim is to convince myself of the ‘whys’ and ‘hows’ of an ambitious set of projects for Summer 2018. The ambition I will motivate in this paper is to design a computer program which interacts with individuals one-on-one over online chat. This program will be linguistically fluent enough to understand what individuals tell it. It will understand what claims its interlocutor uses to support which others, and how one person’s claims may or may not relate to other people’s claims. Its understanding will be culturally formed, dynamic, and learning, with the hope of building a single mind to understand qualitatively many individuals, bridging the gap between qualitative and quantitative sociology.

I am here concerned with how people’s beliefs are structured. That is, what are the mechanisms which govern their adoption and dissolution? How should we represent beliefs, and what exactly is a belief? How do the functions and disfunctions of beliefs interact with their form and application? How should we view discourse as an indicator of held beliefs and mechanism for their modification? I attempt to address these issues in light of prior research in many areas of the social sciences, and conclude with a call to action urging more systematic collection of data regarding people’s belief systems.