Content Analysis Overview

The visible, surface-level information in a text or document.

The underlying meaning or message in a text or document, hidden beneath the surface.

How well the categories used in content analysis accurately measure the concepts being studied.

The percentage of agreement among coders when analyzing the same text or data.

Content analysis strengths, including its ability to analyze large amounts of data, track trends, and examine the presence of specific messages.

A systematic examination of communication materials to find patterns, themes, biases, and meanings.

Focuses on understanding the meaning behind content, often using methods like coding & interpretation.

Analyzes content numerically, by counting pre-determined factors using a system.

Ensuring a document is genuine and what it claims to be.

Consistency in results when analyzing the document.

Important factors to consider when choosing what documents to study.

Availability of documents for analysis.

A set of rules for categorizing and analyzing content.

Key parts of a document/communication for analysis (like themes or words).

Methods for delivering and collecting questionnaires from respondents. Types include self-administered (mail, email, online) and researcher-administered (face-to-face, telephone, online).

Designing a questionnaire for efficient and accurate data collection. Key aspects include question order, preventing response bias, and minimizing non-response.

Questions with only two possible answers, typically 'yes' or 'no'.

Questions that are only asked to respondents based on their answers to previous questions, creating a branching logic.

Questions that present a set of similar options, allowing respondents to choose their answer from a structured grid.

A measurement scale used to gauge the strength of an opinion or attitude, typically using a range of points from 'strongly agree' to 'strongly disagree'.

Questions that allow respondents to provide their own, free-form answers.

Questions that provide a set of predetermined answers for respondents to choose from.

Characteristics or qualities that can vary across units of analysis (people, objects, events). Variables can be manipulated, controlled, or simply measured in research.

A systematic way to collect information from a sample of individuals. It uses standardized questions to gather data on experiences, opinions, and behaviors.

A snapshot of a population at a specific point in time. It collects data from individuals once to understand a phenomenon at that moment.

Tracks changes over time. Data is collected multiple times from the same individuals or groups.

A type of longitudinal survey that tracks changes in a specific population over time. It focuses on the overall trends within the population, not individual changes.

A type of longitudinal survey that follows the same individuals over time. It tracks changes in individual experiences and opinions.

The percentage of people in a survey sample who participate.

When the interviewer's presence or behavior influences the respondent's answers.

Mistakes or inaccuracies in the responses given by survey participants.

The difference between the results of a survey and the true value of the population, due to selecting a non-representative sample.

When respondents systematically provide answers that are not true, leading to inaccurate results.