primary data

Examples of primary data in the following topics:

• Use of Existing Sources

  • But even gathering primary historical documents for each of the three countries would have been a daunting task.
  • Common sources of secondary data for social science include censuses, organizational records, field notes, semi-structured and structured interviews, and other forms of data collected through quantitative methods or qualitative research.
  • Common sources differ from primary data.
  • Primary data, by contrast, are collected by the investigator conducting the research.
  • The primary reason is that secondary data analysis saves time that would otherwise be spent collecting data.

• Summary

  • Two-mode data (often referred to as "actor-by-event" or "affiliation" in social network analysis) offer some interesting possibilities for gaining insights into macro-micro or agent-structure relations.
  • With two-mode data, we can examine how macro-structures (events) pattern the interactions among agents (or not); we can also examine how the actors define and create macro structures by their patterns of affiliation with them.
  • In this chapter we briefly examined some of the typical ways in which two-mode data arise in social network analysis, and the data structures that are used to record and manipulate two-mode data.
  • Our primary attention though, was on methods for trying to identify patterns in two-mode data that might better help us describe and understand why actors and events "fit together" in the ways they do.
  • These methods (best applied to valued data) seek to identify underlying "dimensions" of the actor-event space, and them map both actors and events in this space.

• Objective vs. Critical vs. Subjective

  • Weber took this position for several reasons, but the primary one outlined in his discussion of Science as Vocation is that he believed it is not right for a person in a position of authority (a professor) to force his/her students to accept his/her opinions in order for them to pass the class.
  • The selection of data (this selection reveals data the author believes is reliable whether or not it is)
  • If the researcher decides to collect their own data, then they must:
  • Decide how to measure or categorize the data (if mathematically, what set of parameters counts as a good measure, and if qualitatively what must a category contain)
  • If the researcher decides to use secondary data, this becomes even more complicated.

• Documents

  • The material used can be categorized as primary sources, which are original materials that are not created after the fact with the benefit of hindsight, and secondary sources that cite, comment, or build upon primary sources.
  • Typically, sociological research on documents falls under the cross-disciplinary purview of media studies, which encompasses all research dealing with television, books, magazines, pamphlets, or any other human-recorded data.

• Primary Groups

  • Families and close friends are examples of primary groups.
  • Primary groups play an important role in the development of personal identity.
  • Cooley argued that the impact of the primary group is so great that individuals cling to primary ideals in more complex associations and even create new primary groupings within formal organizations.
  • Relationships formed in primary groups are often long lasting and goals in themselves.
  • This family from the 1970s would be an example of a primary group.

• Analyzing Data and Drawing Conclusions

  • In statistical applications, some people divide data analysis into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA).
  • In an exploratory analysis, no clear hypothesis is stated before analyzing the data, and the data is searched for models that describe the data well.
  • Coding is the process of categorizing qualitative data so that the data becomes quantifiable and thus measurable.
  • How data is coded depends entirely on what the researcher hopes to discover in the data; the same qualitative data can be coded in many different ways, calling attention to different aspects of the data.
  • Coded data is quantifiable.

• Optimization by Tabu search

  • A variation of the technique for valued data is available as Network>Roles & Positions>Structural>Optimization>Valued.
  • This last analysis illustrates most fully the primary goals of an analysis of structural equivalence:

• Ego network density

  • Here is an example of the dialog, applied to the Knoke information exchange data (these are binary, directed connections).
  • Note that there is a line of data for each of the 10 organizations in the data set.
  • Of course, many of the actors are members of many of the neighborhoods -- so each actor may be involved in many lines of data.
  • The idea here is: how much (non-redundant) secondary contact to I get for each unit of primary contact?
  • If reach efficiency is high, then I am getting a lot of "bang for my buck" in reaching a wider network for each unit of effort invested in maintaining a primary contact.

• Gender Inequality in Politics

  • In the primary season, New York Senator Hillary Clinton ran against future President Barack Obama for the Democratic nomination.
  • Data from the 2006 American National Election Studies Pilot Study confirmed that both male and female voters, regardless of their political persuasions, expected men to perform better as politicians than women.
  • The only deviation in this data had to do with competency in areas such as education that are typically perceived as women's domains and voters therefore trusted women politicians more.
  • Because gender is considered to be a master status, or a primary trait around which individuals identify, "women" are considered to be a political demographic.

• Introduction: What's different about social network data?

  • On one hand, there really isn't anything about social network data that is all that unusual.
  • We could look at this data structure the same way as with attribute data.
  • Indeed, many of the techniques used by network analysts (like calculating correlations and distances) are applied exactly the same way to network data as they would be to conventional data.While it is possible to describe network data as just a special form of conventional data (and it is), network analysts look at the data in some rather fundamentally different ways.
  • And, the relations themselves are just as fundamental as the actors that they connect.The major difference between conventional and network data is that conventional data focuses on actors and attributes; network data focus on actors and relations.
  • We will try to show some of the ways in which network data are similar to, and different from more familiar actor by attribute data.