What is social research?

• Social research is the systematic investigation of human behaviours, attitudes, relationships, and social systems in order to produce reliable knowledge and insight
• “Systematic” is the key word: it distinguishes research from casual observation or common sense by following explicit, transparent, and repeatable procedures
• It draws on theory to frame its questions and on evidence to answer them, rather than relying on intuition, anecdote, or authority
• Its aim is not only to describe the social world, but to explain why it works as it does — and often to inform how we might change it

Objectives of social research

• Understand and describe social phenomena — capturing what is happening, to whom, and under what conditions
• Identify causes and consequences of social events — moving beyond description toward explanation
• Predict future societal trends — using patterns in existing data to anticipate what is likely to come next
• Provide a basis for policy — supplying the evidence on which governments, organisations, and communities can act

Types of social research

• Research is usually classified along two distinct axes — not a single list of four boxes
• What kind of data and reasoning?
  • Qualitative — deep, subjective, interpretative; concerned with meaning and experience
  • Quantitative — numerical, statistical, generalisable; concerned with measurement and pattern
• Does the researcher intervene, or only observe?
  • Descriptive — detailing events or situations as they are, without intervening
  • Experimental — testing hypotheses by deliberately controlling and varying conditions
• Because these are different axes, they combine: a study can be quantitative and descriptive, or experimental and qualitative

Inductive and deductive logic

• Research reasons in two directions, and the direction shapes the design
• Deductive — start from theory, derive a hypothesis, then gather data to test it
  • Moves from the general to the specific; characteristic of quantitative work
• Inductive — start from observations, look for patterns, then build theory up from them
  • Moves from the specific to the general; characteristic of qualitative work
• Most real research cycles between the two: today’s inductive insight becomes tomorrow’s deductive test

Qualitative research

• Focuses on human experiences, meanings, and interpretations — how people make sense of their social world
• Common methods include:
  • In-depth interviews — exploring individual perspectives in detail
  • Focus groups — observing how views form and shift through interaction
  • Ethnography — immersing the researcher in a setting to observe behaviour in context
• Produces rich, detailed, contextual data, usually from relatively small samples
• Ideal for exploring new, sensitive, or poorly understood phenomena, where the right questions are not yet clear

Quantitative research

• Seeks to quantify variables, measure how they are distributed, and identify patterns and relationships among them
• Common methods include:
  • Surveys administered to large samples
  • Experiments that manipulate variables under controlled conditions
  • Statistical analyses of existing numerical data
• Produces standardised data that can be summarised, compared, and tested for statistical significance
• With appropriate sampling, provides broad insights that can be generalised to larger populations

Qualitative vs quantitative: a comparison

Discuss: which approach?

• For each question, would you reach for a qualitative or a quantitative design — or both?
  • Why has turnout among under-25s fallen over the last decade?
  • How do first-time voters describe their experience of an election?
  • Does sending a text-message reminder increase the likelihood of voting?
• There is rarely a single right answer — the point is to match the method to the question

The stages of a study

• A piece of research moves through a connected sequence of decisions:
  1. Choose a topic — what is worth studying, and can it be studied?
  2. Design the study — turn the topic into answerable questions
  3. Sample — decide who or what to study
  4. Collect data — gather the evidence
  5. Analyse and interpret — make sense of it
  6. Present — communicate what was found
  7. Reflect — acknowledge the limits
• Each choice constrains the ones that follow — the chain is only as strong as its weakest link

Choosing a research topic

• A good topic is relevant — it speaks to a current societal issue or to a genuine gap in existing knowledge
• It must be feasible: achievable within the resources, time, expertise, and access available to the researcher
• It must be ethical: the potential benefits of the work should outweigh any risk of harm to participants
• A well-chosen topic balances what is interesting, what is answerable, and what is responsible

Research design and planning

• Begins with crafting clear research questions or hypotheses that the study can realistically answer
• Defining the scope: what is being studied, who is included, and when and where the research takes place
• Deciding on methods and data-collection tools that fit the questions — qualitative, quantitative, or a mixture
• The design is the blueprint that connects the research question to the evidence needed to answer it

Variables and operationalisation

• A variable is anything that varies across cases — age, income, turnout, political interest
• Studies often distinguish:
  • the independent variable (the presumed cause)
  • the dependent variable (the presumed effect)
• Operationalisation turns an abstract concept into something measurable
  • “Political engagement” → did you vote?, how often do you discuss politics?, are you a party member?
• How faithfully the measure captures the concept is exactly the question of validity

Sampling techniques

• Probability sampling — every member of the population has a known, non-zero chance of selection (e.g., random sampling)
  • Supports generalisation and statistical inference about the wider population
• Non-probability sampling — participants are chosen by specific criteria or convenience (e.g., convenience, quota, or snowball sampling)
  • Quicker and cheaper, but the risk of bias is higher
• The central concern is representativeness: how well the sample reflects the population it is meant to describe

Data collection methods

• Surveys — gathering standardised information from many respondents through structured questionnaires
• Observations — systematically noting behaviours or events as they occur, with or without participation
• Interviews — direct questioning of participants, ranging from tightly structured to open and conversational
• Archival sources — drawing on pre-existing records, documents, and datasets rather than collecting new data
• The method should fit the question, the population, and the practical constraints of the study

Ethics in social research

• Informed consent — participants have a right to know what the research involves and to agree freely to take part
• Privacy and confidentiality — personal information must be safeguarded and identities protected
• Avoiding harm — researchers must anticipate and minimise any physical, psychological, or social discomfort
• Independent ethical review is now a standard safeguard before data collection begins

Data analysis and interpretation

• Qualitative analysis — identifying themes and patterns of meaning through thematic or content analysis
• Quantitative analysis — summarising and modelling data with descriptive statistics, regression, t-tests, and related techniques
• Analysis turns raw data into an answer to the research question — but an answer is only as trustworthy as the measures behind it

Validity and reliability

• Two qualities determine whether we can trust a measure — and they are easily confused
• Validity — are we measuring what we actually intend to measure? (accuracy)
• Reliability — would the same procedure give the same result again? (consistency)
• Picture an archer’s target:
  • Reliable but not valid — arrows tightly clustered, but off the bullseye
  • Valid but not reliable — scattered around the bullseye, none quite on it
  • Both — tightly clustered on the bullseye
• A measure can be perfectly reliable and still wrong, so both must be established

Presenting research findings

• Communicate clearly — explain results in plain language and avoid unnecessary jargon
• Use visual aids — well-designed charts, graphs, and tables make patterns easier to grasp
• Relate findings back to the original research questions or hypotheses
• Good presentation makes the evidence accessible to its audience, whether academic, policy, or public

Limitations and critiques

• Every study has weaknesses; acknowledging them openly is a mark of good research, not a failure
• Researchers should be open to feedback and critique from peers, reviewers, and the wider community
• Identifying limitations points the way forward, clarifying what future research should address
• Honesty about limits is what allows knowledge to accumulate and improve over time

Conclusion

• Methodology matters: the quality of our conclusions depends on the quality of our methods
• Social research is an evolving practice — new data sources, tools, and techniques continually reshape what is possible
• The choices made at each stage — topic, design, sampling, collection, analysis, presentation — are connected and consequential
• We followed one question — why young people vote less — from a vague idea to a defensible, if imperfect, answer; every study makes that same journey
• Questions and discussion are welcome