11  Introduction & Theory Chapter

11.1 The Abstract

Although it appears first in your thesis, the abstract should be the last section you write. It concisely summarizes:

  • The reason for the study and the research question or hypotheses
  • The method used
  • The key findings
  • The main conclusion

Keep it to approximately half a page. Focus on the most important points and do not include citations.

TipThe Perfect Abstract

Check out this resource for how to write a top-notch abstract: https://www.nature.com/documents/nature-summary-paragraph.pdf

11.2 The Introduction

The introduction introduces the reader to your thesis. It presents your topic and frames the study by providing its scientific and societal relevance. A good introduction is concise and focuses on two questions: “What has been done in this area?” and “Why is the current study useful?”

11.2.1 Standard structure

  1. Reason (aanleiding): Why is this topic relevant now? What social or scientific development motivates this study?
  2. Topic introduction and knowledge gap: Briefly introduce the topic and name the gap in existing research (keep it short here; details follow in the Theory chapter)
  3. Problem statement: Articulate the specific research problem
  4. Research question: State the central RQ explicitly and clearly
  5. Societal and scientific relevance: Explain why answering this RQ matters

For qualitative research, also briefly summarize your methodology (e.g., grounded theory) and methods (e.g., interviews, thematic analysis) at the end of the introduction.

11.2.2 Example introduction

Mattis and colleagues (2025, Journal of Communication) begin their article on nudges in news recommenders with a statement on societal relevance:

In recent years, there has been a growing interest in the notion of “democratic news recommender design” (Helberger, 2019; Mattis et al., 2024b; Mitova et al., 2023; Vrijenhoek et al., 2021). Drawing on nudge theory (Thaler & Sunstein, 2009), this line of research posits that news recommender systems can be viewed as choice architectures, where decisions on how to select, rank, and present news items can have implications for how people engage with and process news content (Knudsen, 2023; Mattis et al., 2024b). This may have positive downstream effects on democratically relevant outcomes, such as citizens’ political learning, political participation, or tolerance (Helberger & Wojcieszak, 2018; Mattis et al., 2024b).

Their argument is basically that news recommenders needs to be better understood because they can influence how people learn about the world and thus participate in democracies.

They then move on to outline the research gap:

As of now, work on democratic news recommender design is still in its infancy, as many studies predominantly focus on conceptualizing potential approaches (Lorenz-Spreen et al., 2020; Mattis et al., 2024b; Vrijenhoek et al., 2021) and their ethical implications (Vermeulen, 2022). These studies often point to the potential of diversity-aware recommender design or nudging, but rarely test these assumptions (for exceptions see Heitz et al., 2022, 2023; Mattis et al., 2024a). Moreover, while the effects of democratic news recommender design are likely to transpire over longer periods of time, there are still rather few longitudinal research studies (for long-term studies that are an exception to this, see Heitz et al., 2022, 2023; Lee & Suh, 2022). Hence, we still know little about how nudging news engagement works over extended periods of time.

They denote that experimental work in this area, particularly over longer periods of time, are missing.

Last, they explain how their present work addresses this app, while simultaneously summarizing the research design already:

To provide more realistic insights into the promises of democratic news recommender design, we conducted a preregistered seven-day long field experiment with Informfully (Heitz et al., 2024a),1 a fully customizable content delivery platform that we used to mimic a news aggregator app; Informfully can be downloaded directly from Google Play and the iOS app store and provided respondents with a realistic news use experience, thereby maximizing external validity. Within this externally valid news aggregator app, we tested how a position nudge and accessibility nudge affect (a) the selection of, (b) the engagement with, and (c) the learning from environmental news. The position nudge denotes the deliberate prominent positioning of a particular article, whereas the accessibility nudge describes changes to an article that make its content easier to understand by lowering its syntactic text complexity.

11.2.3 Checklist for the introduction

11.3 The Theory Chapter

The theory chapter reviews the relevant literature and major theories, shows how your research builds on existing work, and leads to your hypotheses (or sub-questions for qualitative research). It is of utmost importance that it guides the reader towards the key goal (i.e., testing the hypotheses, answering the research questions). It should represent a logical rationale, not just a mix of found studies and summaries of their findings.

11.3.1 Structure

A theory chapter typically:

  1. Defines and explains the central constructs/concepts
  2. Builds a theoretical argument for the relationships between constructs
  3. Discusses relevant prior empirical findings
  4. Combines both theory and empirical findings into a coherent rationale for your study
  5. Culminates in clearly formulated hypotheses (or sub-questions) and a conceptual model

Each sub-section should follow a cone shape: start with general definitions and background, then narrow to specific relationships relevant to your hypotheses.

TipThe golden thread

Your research question should be “visible” in every paragraph of your thesis. Whenever you are unsure whether a paragraph belongs, ask yourself: does this contribute to answering my research question? If not, it probably should not be included!

11.3.2 Example theory section

At the end of the first part of their paper, Schemer et al.. (2021) write e.g., the following:

Taken together, previous studies are inconclusive with respect to the overall relationship between the frequency of Internet or SNS use and subjective well-being. Some Internet applications or modes of use may be beneficial while others may be detrimental. A look at reviews and meta-analysis that summarized the primarily cross-sectional evidence suggests that studies documenting negative relationships outweigh those that found positive relationships (Huang, 2010; Steers, 2015). This finding may reflect that passive use of Internet applications is dominant (Escobar-Viera et al., 2018; Verduyn et al., 2015) or that processes that are detrimental to subjective well-being (negative feedback, upward comparisons, displacement of offline relationships) occur more frequently than processes that produce positive outcomes (positive feedback, building social capital, engage in identity exploration) when using Internet application like SNS (de Vries & Ku¨hne, 2015; Haferkamp & Kra¨mer, 2011).

From this, they deduce the following hypothesis in this way:

Facing these negative net effects, the present study starts from the following between-person hypothesis (H1): Frequency of: (a) Internet use in general; and (b) SNS use in particular are negatively related to subjective well-being (between-person correlation).

WarningNot just a summary of existing literature

A good theory section present theoretical arguments that are supported by the existing literature and thus serves to rationalize the hypotheses. It is not a unstructured list of some related findings!

11.3.3 Content checklist

11.3.4 Structure and writing checklist

11.3.5 Vocabulary and references

11.3.6 Hypotheses checklist

11.4 References

  • Mattis, N., Heitz, L., Masur, P. K., Moeller, J., & van Atteveldt, W. (2025). Nudges for news recommenders: Prominent article positioning increases selection, engagement, and recall of environmental news, but reducing complexity does not. Journal of Communication. https://doi.org/10.1093/joc/jqaf019

  • Schemer, C., Masur, P. K., Geiss, S., Müller, P. & Schäfer, S. (2021). The impact of Internet and Social Media Use on Well-Being: A Longitudinal Analysis of Adolescents Across Nine Years. Journal of Computer-Mediated Communication, 26(1),1–21. https://doi.org/10.1093/jcmc/zmaa014