Call & How to DOCA

DOCA USER MANUAL

New to DOCA? Our user manual provides a practical introduction to the Database of Variables for Content Analysis (DOCA). It explains the structure of the database, how individual entries are organized, and how researchers, students, lecturers, and contributors can make the most of the platform.

The manual includes step-by-step examples for:

  • Finding suitable variables and operationalizations for content analysis
  • Using DOCA in teaching and classroom settings
  • Contributing new variables and becoming a DOCA author
  • Understanding key concepts such as variables, constructs, codebooks, and reliability

Whether you are conducting research, teaching content analysis, or exploring standardized operationalizations, this guide will help you navigate DOCA efficiently and effectively.

Download the DOCA User Manual (PDF).

 

ROLLING CALL
DOCA aims to become a comprehensive research tool for variables. Therefore, we are calling for contributions to DOCA in two ways:

  • Option 1 – Adding a new variable: You can submit an entry for a variable that has not been previously captured in the database. After a successful review process, the variable will be entered in the corresponding section of the database.
  • Option 2 – Adding operationalizations to an existing variable: You can submit an entry that adds an operationalization to a variable that has already been recorded in DOCA. In this case, a new entry marked as "addition to variable XX" will be created. The existing entry must be referenced and linked to.

Review

To ensure quality, all isubmissions  are reviewed by at least two editors.

Please send your suggestions for further variables to be added to the database to (sabrina.h.kessler@foeg.uzh.ch) at any time. Please note the submission guidelines below:

SUBMISSION GUIDELINES

Selection of Variables:

The author(s) of each database entry decide(s) which example operationalization is choosen. However, to be consistent, authors are asked to consider the following criteria:

  • Topicality
  • Relevance (possible indicators: citation frequency, expert opinion, ...)
  • Accessibility of variables
  • Quality (reporting of reliability coefficients)

Structure:

  • Each Database entry follows (more or less) the following structure:

1. A brief description of the variable or construct

2. A brief description of the most common field of application / theoretical foundation

3. (If applicable) References/combination with other methods of data collection

4. Sample operationalizations including

  • information about the selected study (research question/s; analyzed medium)
  • information about the variable or construct (level of analysis, reliability score, categories/values)
  •    5. (If available) (links to) the Codebook / Protocol / Dictioniaries or other relevant material

Section:

Please specify to which section (Basics & Procedures; News / Journalism ;  Fiction; Entertainment; /User-Generated Content, Variables for Automated Content Anaslysis)  the contribution belongs.

Type of Entry:

Please specify whether you submit an entry for a) a new variable oder b) an existing variable.

Length

Each of the entries should consist of between 1,000 to 1,500 words, all included. The count includes the full text, notes, references, figures, illustrations, and tables.

Language:

Preferred English. But: Use original language of the operationalization. If applies: Use gender neutral language, e.g. He/She;  Autor*Innen

Citation Style

APA 6th

Copyright

Please make sure that there are no copyright infringements when citing the operationalizations. This means that the operationalization must be published (check also databases like Gesis, Fors...)  and therefore quotable or you have obtained the rights for the publication from the author (we will send you an author's permission template asap).

 

GLOSSARY (based on Kessler et al., 2023 1)

Construct: Latent theoretical concepts that researchers aim to measure empirically

Variable: An operationalized category used to classify and measure aspects of a construct. A variable is a characteristic of the object of analysis that is to be examined in the course of the analysis. There are formal variables, such as date or genre, as well as content-related variables, such as the actors who speak or the positions expressed.

Value: Distinguishable and exhaustive categories or expressions a variable
can take; values should always be mutually exclusive.

Codebook: A document containing definitions of constructs, variables, values
and detailed coding instructions.

Reliability: A measure of the consistency and reproducibility of coding results. In manual content analysis, reliability refers to the extent to which different coders achieve similar results under comparable conditions (intercoder reliability). In automated content analysis, it refers to the stability and consistency of computational coding procedures across repeated applications.

 

1 Kessler, S. H., Sommer, K., Humprecht, E., & Oehmer-Pedrazzi, F. (2023). Manuelle standardisierte Inhaltsanalyse. In F. Oehmer-Pedrazzi, S. H. Kessler, E. Humprecht, K. Sommer, & L. Castro (Hrsg.), Standardisierte Inhaltsanalyse in der Kommunikationswissenschaft – Standardized Content Analysis in Communication Research: Ein Handbuch—A Handbook (S. 9–21). Springer Fachmedien. https://doi.org/10.1007/978-3-658-36179-2_2