Extensive summary in question format Research Methodology II International Business Communication
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Course
Research Methodology II (LETCIWB265IBC2021PER_3V)
Institution
Radboud Universiteit Nijmegen (RU)
Book
Introducing Communication Research - International Student Edition
Clear and complete summary of all the content of the course. The summary consists of formulated questions about all the Key Readings and content of the lectures. I always summarized the Key Readings before the lecture and then added notes from the lecture in my summary.
Pre- Master CISS: Summary Introducing Communication Research - Methodology (800892-B-6)
Methodology for premaster Communication and Information Sciences summary
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International Business Communication
Research Methodology II (LETCIWB265IBC2021PER_3V)
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31-1
Preparation Lecture I: Treadwell & Davis Chapter 11
What is content analysis (or corpus analysis)?
Research technique for the objective, systematic, and quantitative description of the manifest
content of communication.
- Quantitative : we must count occurrences of whatever we are interested in.
- Systematic : we must count all relevant aspects of the sample. We cannot arbitrarily
pick what aspects get analysed. (rigid)
- Objective : we select units for analysis and categorize them using clearly defined
criteria. (validity, reliability, clear unit of analysis)
- Manifest : tangible and observable. (not latent)
What sort of content can be used for content analysis?
Content analysis can be used with almost any form of content (press, radio, web billboards,
license plates). It has been used to study representations in news, advertising, and
entertainment media of demographic, social, minority, and occupational groups as well as of
health, parenthood. The contexts of content analysis range from and individual’s
communication through interpersonal, group, and organizational communication.
What are the advantages of content analysis?
- Unobtrusive (human participants are not involved)
- Emphasis on systematic sampling, clear definitions of units, and counting
What are the disadvantages of content analysis?
- It addresses only questions of content.
- Method mostly has application if used for comparisons (e.g. how does the frequency of
patriotism in candidate X’s speeches compare with the frequency of that word in candidate
Y’s?)
- Validity, problematic in terms of relating its finding to the external world. (e.g. the same
frequency of the word patriotism, but another meaning)
How to examine words in their context?
Define our units of analysis as sentences or paragraphs rather than words and then code each
sentence or paragraph as positive, negative, or neutral with respect to the word.
How can traditional content analysis be summarized?
Assigning units of content to predetermined categories and then counting the number of units
in each category.
What are the steps of content analysis?
1. Develop a hypotheses/research question about communication content
2. Define the content to be analysed (limit the content to be studied!)
3. Sample the content (which sampling method?)/create your corpus
4. Select units for coding
5. Develop a coding scheme (classification system or categories)
6. Assign each occurrence of a unit in the sample to a code in the coding scheme/annotate the
corpus
,7. Count occurrences of the coded units
8. Report results, patterns of data, and inferences from data
Why are most content analyses more complex in practice?
For starters, questions related to the type of sample and size of sample become more complex.
Content analyses focus typically on more lengthy content. This content may be more complex
in that in may include graphics, animation, video and audio. This complexity necessitates
serious thinking and planning about units of observation and units of analysis. Analysists also
have coding decisions. And there is the question of coding units and the question of inference.
How do coding decisions work?
Whether to establish coding categories on the basis of theory prior to the study, or whether to
allow categories to emerge as the study progresses.
What is the question of coding units?
Code on sentence level or for example code in terms of major topical issues.
What is the question of inference?
The results of an analysis are important, but more important are the inferences drawn from
these results. Analysts have to develop evidence and arguments that relate their content
findings to a given theoretical interest. Important in this process are the prior steps, such as
conducting a literature review, seeking theoretical grounding, developing research questions
and sampling procedures. These steps should help support the inferences the analyst is trying
to draw about the relationship observed between content and human behaviour.
What is interaction analysis?
Capture and understand interactions among members of a group and the different roles that
group members play. He outlines three broad categories of group behaviour: task-oriented,
group-oriented, self-centered behaviour.
What are the advantages of content analysis of the web?
Ready and inexpensive access to a huge diversity of content from a variety of media types and
sources worldwide. It offers the potential to analyse the dynamics of human interaction as
well as traditional content such as documents.
What are the disadvantages of content analysis of the web?
Given the availability of software that can capture and analyse an entire population of content,
the question whether to sample at all arises. Web content may be ephemeral (constantly
update) which raises the question of when to record and sample content. The size raises
problems of sampling and achieving. The complexity raises problems of processing not only
text but also audio, video etc. The ephemerality raises problems of data capture, sampling,
and the possibility of the researcher missing important content altogether. Also the relation
between the sample and the population from which it is drawn is not fully known. The data
may be incomplete or biased.
What is a particular concern for content analysis?
The ability of software to recognize and analyse the subtleties of human language and
meaning, for example, humour. Against that is the potential for computer analysis to identify
aspects of content that a human analyst with human biases may not identify.
, What are the two starting points for acquiring web content?
Using existing content or build your own body of content (web scraping, web crawling).
Acquiring content may be more or less difficult depending on the nature of the sources.
What is disambiguation?
The process of examining a word in its context and assigning it the most appropriate out of
several possible meaning. Without training in disambiguation, software will be unable to
distinguish between words.
How can computer analyses can be simplified?
By stemming, lemmatization, and the removal of stop words. Stemming means changing all
variations of a word to its basic stem. Lemmatization means grouping words together based
on their basic dictionary definition so that they can be analysed as a single item.
How can content analysis be both quantitative and qualitative?
They may coexist in any given study and the dividing line between the two may be thin. Also
a distinction between the phenomena studied ant the analyses applied to them can be made.
When should be made use of qualitative analyses?
When the analyst seeks to interpret or critique a body of content or to investigate in depth
beyond what some might argue is the superficial and reductive counting of quantitative
analyses.
Guest lecture 2-2-2022
Student course Research Data Management (RDM)
Henk van den Heuvel, Data Officer, Faculty of Arts
What is research data?
Research data is all information, digital and non-digital, generated as part of the scientific
process, on which scientific conclusions are based.
Is data a straightforward concept?
In some disciplines it is, such as survey data, interview transcripts and statistical data. For
other types of data this is less clear.
- Data as part of a publication: extensive, structured reference lists may be valuable databases
on their own, and could/should be archived in a data repository.
- Primary data: audio/video/text data that you collected/recorded yourself, raw data.
- Secondary data: derived data, e.g. analysis schemes, scripts and codebooks.
- Annotations: may be databases on their own, and could/should be archived in a data
repository (check copyright if the original text is included).
Why research data management?
- formal need to comply: RDM certificate is part of PhD thesis
- saves time and increase efficiency
- keeps your data safe and secure
- avoids data loss
- prevents unauthorized access
- facilitates the documentation and reuse of data
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