FIELD METHODS-Midterms

Content Analysis

It is a research method used to systematically analyze the content of communication (such as text, speech, images, videos, or social media posts)

Content Analysis

It is use to identify patterns, themes, meanings, or frequencies of certain words, ideas, or symbols

1. To identify recurring themes and patterns.
2. To quantify qualitative data.
3. To understand social and cultural influences on behavior.
4. To track changes over time.
5. To provide insights for interventions and policies.

Purpose of Content Analysis in Psychology

Conceptual analysis
Relational analysis

General Types of Content Analysis

Conceptual analysis

focuses on identifying and counting the presence of certain concepts, words, or themes in a text

Conceptual analysis

A researcher analyzes 200 social media posts about stress among university students

Conceptual analysis

They code how many times the words “stress,” “burnout,” “anxiety,” or “pressure” are mentioned

Relational analysis

goes beyond just counting words or concepts

Relational analysis

It examines how concepts are related to each other within the text, focusing on the context and relationships between themes

Conceptual analysis

The goal is to see how often specific ideas appear to measure their significance

Relational analysis

The same researcher studies how “stress” is connected to other terms in the posts

Relational analysis

Example is “Stress” often co - occurs with “time management” and “lack of sleep.” and “Anxiety” is frequently linked to “exams” and “internet connection issues”

1. Systematic and Rule- Governed

2. Objective and Reliable

3. Both Quantitative and Qualitative

4. Content-Focused

5. Flexible Sources of Data

6. Non-Intrusive Method

7. Contextual and Interpretive

8. Replicable and Transparent

9. Reductive

10. Versatile and Interdisciplinary

Characteristics of Content Analysis as a Research Method

Quantitative Approach

A research approach that focuses on counting, measuring, and statistically analyzing the frequency or occurrence of certain words, themes, or categories within communication content.

Quantitative Approach

(Numbers, frequency, measurement)

Quantitative Approach

It answers “how much” or “how often.”

Qualitative Approach

(Meaning, interpretation, themes)

Qualitative Approach

A research approach that focuses on the meaning, context, and interpretation of communication content

Qualitative Approach

It explores latent content (the underlying message, emotions, or themes) rather than just frequencies

Content Analysis in Research

is studying communication content in a systematic way to uncover hidden patterns, meanings, and trends.

1. Define the research question.

2. Select the material (e.g., newspapers, interviews, TV ads, social media posts).

3. Develop categories or codes (keywords, themes, symbols).

4. Analyze, interpret patterns in the data and apply the categories systematically

5. Draw conclusions about the messages or meanings.

Steps in Content Analysis

Unobtrusive data collection

Transparent and replicable

Highly flexible

Content analysis is a readily-understood and an inexpensive research method

Advantages of Content Analysis in research

Unobtrusive data collection

Content analysis allows researchers to study behavior, attitudes, or cultural patterns without directly interacting with participants

Unobtrusive data collection

This reduces bias, as participants are not influenced by the researcher’s presence

Transparent and replicable

Content analysis uses clear coding rules and systematic procedures.

Transparent and replicable

This means other researchers can repeat the study, check the coding categories, and verify results. It strengthens reliability and scientific credibility

Highly flexible

Content analysis can be applied to different types of data (text, images, videos, social media posts, interviews) and adapted for quantitative (counting) or qualitative (interpretive) purposes

Content analysis is a readily-understood and an inexpensive research method

Content analysis is relatively easy to grasp compared to more complex research methods because it involves examining texts, documents, or media that are already available

Reductive

Subjective

Time intensive (Can be extremely time consuming)

Can be difficult to automate or computerize

Disadvantages of Content Analysis in research

Reductive

Content analysis often reduces rich, complex human communication into categories or codes

Reductive

This makes data manageable, it can oversimplify meanings and miss nuances (especially in emotions, sarcasm, or cultural context)

Subjective

Content analysis almost always involves some level of subjective interpretation, which can affect the reliability and validity of the results and conclusions, leading to various types of research bias and cognitive bias

Time intensive (Can be extremely time consuming)

Developing coding categories, training coders, and systematically analyzing large amounts of text, images, or videos can be very time-consuming

Can be difficult to automate or computerize

Automated software can help but often lacks subtle human interpretation

Can be difficult to automate or computerize

Automated analysis may miss sarcasm, metaphor, or emotional subtleties, leading to inaccurate or incomplete findings

To transform unstructured communication into structured analyzable data, allowing researchers to better understand human thought, emotion, and behavior in real-world contexts

The purpose of content analysis in psychology

Causal Comparative (Ex Post Facto) Design

investigates cause-and-effect relationships by comparing groups that already differ on an independent variable that the researcher cannot manipulate

Causal Comparative (Ex Post Facto) Design

This design aims to discover the reasons for existing group differences or the consequences of an event that has already happened.

Causal Comparative (Ex Post Facto) Design

This "after the fact" method is useful for studying phenomena where manipulation isn't possible but is limited by a lack of control over the independent variable and random assignment, making it difficult to establish definitive causality

Ex Post Facto design

is a nonexperimental research design where the researcher examines the effect of an independent variable after it has already occurred, without manipulation or random assignment

Retrospective analysis
Non-manipulation of variables
Focus on preexisting conditions
Inference of causality

Key characteristics of ex post facto research

Retrospective analysis

The study begins after the phenomena or event of interest has occurred

Non-manipulation of variables

The researcher does not change or assign the independent variable (e.g., weight, school type) to participants

Focus on preexisting conditions

The study groups participants based on characteristics they already possess

Inference of causality

The researcher aims to infer a cause-and-effect relationship, but with less certainty than a true experiment, as there is no random assignment

Correlational Studies
Criterion Group Studies

Two Main Types Of Ex Post Facto Research Designs

Correlational Studies

that aim to identify antecedents of a present condition

Correlational Studies

Example is the connection between stress and future job performance

Correlational Studies

Example is positive relationship between temperature and ice cream sales

Criterion Group Studies

that discover possible causes by comparing groups with and without the variable of interest

Criterion Group Studies

Example is research comparing job performance of skilled versus unskilled workers

Criterion Group Studies

Example is depressed and non -depressed individuals

1. The inability to establish definitive causality
2. The lack of random assignment and variable manipulation, a higher risk of third variables
3. The potential for inaccurate or incomplete data

Limitations of Ex Post Facto Research

1. Ethical advantage

2. Practical and feasible

3. Explores cause-and-effect relationships (tentatively)

4. Generates hypotheses for further research

5. Applicable across disciplines

Importance of Causal - Comparative (Ex Post Facto) Design