Content Analysis - Science topic

please here the voice reply

Dear Erika Arias Bustos ,

QuillBot's AI content detector tool is trained with advanced algorithms to identify repeated words, awkward phrases, and unnatural flow, which are key indicators that the content is AI-generated.

Regards,

Shafagat

I would seriously doubt that you would be able to ensure the reliability and validity of such a coding scheme? But before even trying, I would recommend that you look at the research methods literature on the reliability and validity of content analysis. Sorry to be so discouraging.

هذا قريب جدا من مفهوم الحقول الدلالية القائمة على مبدأ التقارب الدلالي... هذا المسلك مفيد في اختزال الخطاب في رواق عام مهيمن، وفي مسالك عامة مساعدة في بناء الدلالة.

Thank you, Liam. I cannot wait to read the article. Thanks again.

I wonder, whether qualitative content analysis also has coding.

Qualitative content analysis is a valuable research method used in public administration to delve into policy processes, program evaluation, governance dynamics, organizational culture, and comparative analysis. Through the systematic examination of textual data, researchers can uncover deep and nuanced insights into the complexities of public administration phenomena.

Following. That's an interesting topic. Practical considerations: Are you going to use only digital versions? Are you going to actually READ all digital stories? Are you going to scan and digitize? You will need stories published in different eras to be able to diachronically compare gender representation shifts.

Conducting a content analysis of focus group interviews conducted before a scale adaptation study for your doctoral thesis can be beneficial. It can help in identifying common themes, patterns, and insights from the participants' responses, providing valuable context for the scale adaptation process. Content analysis can also assist in refining the scale's items, ensuring they capture the relevant constructs accurately. Additionally, it can enhance the credibility and rigor of your research by demonstrating a systematic approach to data analysis. Overall, while not always necessary, conducting content analysis can significantly enrich the quality and depth of your thesis.

Hello, I try to answer your question and my answer is open to any comments and critiques. Please chek them, if there is any to ensure that my answer would not be misleading.

Content analysis is a very general term which refers to various methods and theories methods are based on. It can even refers to any analysis of content, sometimes regardless of its from (written or visual), that aims to find out characteriestics of content. It can basically classified into quantitative and qualitative ones.

In your case, you mentioned two terms, discourse and codebook. As far as I know, discourse analysis seems to be a qualitative one. Therefore, your mention of codebook is a little bit confusing. Since I am not sure about which kind of method (quantitative/qualitative) you plan to use for the content analysis, I can only provide a solution based on my experience, which is only quantitative one.

The nature or key logic of quantitative content analysis is to deductively identify features of content (which time are superficial most of the time, such as frequency of word, length of text, source, etc.) that are a priori in existing literature. This is why you need a codebook for your analysis.

Therefore, I would guess that, if you tend to conduct a quantitative content analysis, which is quite similar with framing analysis that I did before, you might follow the steps as follows:

1. Sampling and decide the unit of analysis. Check some textbooks of social science research method, or those about communication studies (in which I guess you major, thus I will recommend at the end) and decide which strategy of sampling that suits your research objectives and that is within the scope of your condition. Also, decide the unit of analysis, it can be a news item or a whole web page, which also depends on your objectives. The decision of unit of analysis is relevant to your question about webpage, make sure that you find a suitable one. For example, since there are too much information in which there are much that you do not need. You can make each single news item or one twitt, if you analyze social media. Also, I think the form of news item (newspaper, broadcasting, TV, social media, etc.) has nothing to do with your analysis because all data that you need is written instead of visual or audio.

2. Identify categories, which refers to features of content and in your case, from existing literature or propose some categories yourself based on the requirement of your research questions and identify definition of each category, which is the basis of your codebook.

3. Make a codebook with the definitions that you settle beforehand. The function of codebook is to help you find categories (it can be topics, or frame in news coverage).

4. Conduct conduct inter-coder reliability tests until the result is applicable. This step is to make sure the objectivity and replicability of your study, in other words, anyone would get the same or very similar results if they used your codebook.

5. Start coding, namely finding the categories based on the definitions in the codebook and if the definition is not clear or there is new categories, revise the codebook, conduct inter-coder reliability tests until there's acceptable result and start the coding again with the revised codebook.

6. Now you have your data, namely the number of each category in each unit of analysis. As you said your objective is to find the evident ones, I would guess that you need to calculate the frequencies of the categories in all your sample and figure out the ones with the frequencies you need.

7. You mentioned that you want to find 'moral' discourse, you might need to identify some value judgements from the content. However, it is very hard to do so through a quantitative content analysis because you can never know how the value judgements are expressed before coding. In this case, you cannot pose a definition of such value-laiden categories or your definition would be vague and thus hard for practice. Please do pay attention to this issue and add some qualitative analysis to find the deeper meanings with value in the content where you identified categories.

Etnografia, é olhar, ouvir, observar e anotar em detalhes. Se me exigem um método teórico, cito meu capítulo no Gate: "Método de pesquisa qualitativa na obra antropológica de Cãmara Cascudo"

Thanks dear Chuck A Arize for your suggestion. I'm currently using MAXQDA.

Thanks, but your reply ignores the content of my post.

Selecting the right tool (e.g., NVivo software or others) depends on the objectives of your study. However, for financial statement analysis, you may use horizontal, vertical, and/or ratio analysis, among others.

The following paper could help you out in this regard:

Corporate governance and voluntary disclosures in annual reports: a post-International Financial Reporting Standard adoption evidence from an emerging …‏

RN Boateng, V Tawiah, G Tackie - International Journal of Accounting …, 2022‏ - emerald.com‏

In a directed content analysis, you construct a pre-determined codebook from an existing theory or other explanatory framework. This kind of content analysis is usually relatively quantitative, and typically relies on counting codes.

Are you thinking of machine learning and natural language processing? If so, conduct an academic search for both terms together. There is a learning curve.

Hi,

The NCapture extension may miss Twitter images due to its limitations and Twitter's content loading style. Duplicate references could result from NCapture and NVivo treating retweets, quote tweets, or metadata as separate entries. Less than 100% NVivo coverage might be due to challenges in interpreting complex PDF elements or low-quality text.

Qualitative content analysis (QCA) and discourse analysis (DA) are both used in qualitative research to analyze textual data. They have similarities but also differences. QCA focuses on identifying patterns and themes in the content, while DA examines language use in broader social contexts. QCA smaller units, while DA looks at larger units of text. Content analysis uses structured coding schemes, while discourse analysis takes an interpretive approach. They can be used together in research.

Gillian Mccarthy ultimately all qualitative research analysis includes inductive and deductive components. What you described would be twofold: (1)begin with a deductive analysis focused on the 5 areas from your framework. Within this process, you would want to keep your mind open to include ideas that do not align with the framework--that is, if an idea keeps coming up in the transcripts but does not fit in one of the 5 areas, then I recommend putting these data in a separate 'category' or code depending on how you are capturing your analyses processes. (2) your second step is to identify the patterns within each of the 5 areas. In this step, you are combining data that are similar in meaning. The goal is to combine the data until you get to between 2 and 5 groups. You would also do this step for any group of data that emerges outside of the framework.

See the documents attached. I hope this helps.

Veronica

Content analysis and thematic analysis are two widely used methods of qualitative data analysis in research . While they can be used for similar data sets, there are distinct differences between the two methods.

Content analysis is a systematic approach to analyzing the content of text-based data. This method involves organizing and categorizing data into specific codes or categories based on predetermined criteria. Content analysis can be either quantitative or qualitative, but it is commonly used for quantitative research. The aim is to identify and quantify patterns, themes, or trends in a large amount of data.

On the other hand, thematic analysis is a method of analyzing qualitative data. This method involves identifying and analyzing patterns or themes that emerge from the data itself. Unlike content analysis, thematic analysis does not rely on predetermined categories and codes. It is a more flexible and inductive approach to data analysis, allowing themes to emerge directly from the data. Thematic analysis is a more interpretive and nuanced approach to data analysis, with a greater emphasis on the context in which the data was produced.

Overall, the main difference between content analysis and thematic analysis is that content analysis is more focused on quantifying patterns and trends in data , while thematic analysis is more focused on understanding the meaning and context of the data.

Jamie Njue I sent your question to chatGPT, could any of this help?

There are many free tools available for content analysis. Here are a few suggestions:

All these tools are free, and they can be useful for analyzing news articles and other types of texts.

Both content analysis and thematic analysis are methods for analyzing qualitative data, but they differ in some key ways.

Content analysis involves systematically categorizing and quantifying the content of a communication, such as speech, writing, or visual media. This can involve coding the content of the communication according to specific predefined categories. For example, in a study of gender stereotypes in film, content analysis might involve coding the gender of each character, or categorizing types of dialogue as reinforcing or challenging gender stereotypes.

Thematic analysis, on the other hand, involves identifying and analyzing recurring patterns or themes within qualitative data. This process is more interpretive and less focused on categorization and quantification than content analysis. For example, in a study of gender stereotypes in film using thematic analysis, a researcher might identify key themes related to the representation of women and analyze how they are portrayed in the film.

Both content analysis and thematic analysis can be considered types of textual analysis, which is a broader category of methods that involve analyzing written or spoken language or other forms of text.

For your dissertation, given your research question, it sounds like content analysis might be a good fit, as you are interested in analyzing the content of the film in a systematic way to identify how gender stereotypes are both challenged and reinforced. You may want to consider developing a coding scheme to categorize different aspects of the film's content, such as the gender of characters and types of dialogue. However, it's ultimately up to you to choose the most appropriate method based on your research question and the data you will be analyzing.

Thank you Ajit for your detailed response. I am struggling to find a way of contacting the companies at the moment, so that is my current task. It is my ethics panel that require I try and gain permission, so I am hoping that other researchers who have gained permission may have some guidance on who to contact. Your suggestions of points to include when I do make contact are very helpful, thank you. I had mistakenly assumed that reviews would be classed as in the public domain and it would therefore be appropriate to just cite and reference their origin.

There is little point in double-coding your data to find out whether you agree with yourself. The whole point of inter-rater reliability is to determine whether two coders can consistently apply the same coding system.

A lot depends on whether you are planning on publishing your work and if so where.All too often, reviewers will insist on an assessment of the reliability for your coding even when the coding system is quite straight forward.

One compromise is to have a second coder work on only a subset of the data, say 10% or 20%.

Thank you so much Digo Chakraverty Shahram Sedghi both pieces of your advice are very helpful and they gave our team new insights on how to go through with the methodology of our research

Yes, it is possible to utilize multiple analytical methods in one article. In fact, using multiple methods can provide a more comprehensive understanding of the research question or topic. In your case, combining discourse analysis and content analysis can help you gain insights into both the content and the communication patterns in the classroom interactions. To handle the two methods in your article, you can start by clearly defining each method and explaining why you chose to use them. Next, you can describe how you applied each method to the data, including any specific software or tools you used. You should also provide examples of the themes and categories that emerged from each method. When interpreting the results, you can discuss the similarities and differences between the two methods, and how they complement each other. For example, you can discuss how the content analysis provided information about the topics discussed in the classroom, while the discourse analysis helped you understand the power dynamics and social interactions between the teachers and students.

Muy agradecido con usted maestra Cristina Zourna por atender la pregunta que recién hice. Indagaré en la fuente de información sugerida por usted. Gracias.

There are several different options within the label "thematic content analysis," depending on the extent to which you relied on counting codes or a more interpretive approach. So can you tell us more about how you conducted your analysis and what your research questions/goals were?

I agree that we need more information about the approach to content analysis that you are using. In particular, what is your purpose for creating a codebook -- do you want to do systematic counting with your codes, or are you aiming for a more interpretive analysis?

https://psyarxiv.com/ is common for psych, but if your goal is to get a lot of readers, with any of these it will be helped by posting links on social media. As since we are on ResearchGate, you can post here too.

Depending on the type of research you are conducting, you may need to combine theories from different areas to strengthen the analytical argument. For example, if you are working with discourse adjustment in contexts of social dynamics in different groups, you may need to combine critical discourse analysis (van Dijk) with social representation theory (Moscovici). I also recommend checking out some studies on social representations of language (Bernstein).

Quantitative versions of content analysis place an emphasis on validity and reliability, and both of these concepts require another variable that correlates with the one you have measured. In the case of validity, this should be something related construct validity, such as discriminant or convergent validity, which could be some variable other than the data from a second coder.

Reliability, however, requires two separate measures of the same thing, so I cannot see you could assess reliability without a second coder. You could, however, claim that the coding system has such a high degree of "face validity" that a second coder is not necessary.

Lucie Marchand yes you can — it depends on the research objectives.

I would be inclined to include all of the attributes.

However, research methods flow from research questions. Your research questions may provide insight into which strategy to use. Do you best answer your research questions by including all attributed or just one dominant attribute per source text?

Any data collection that occurs at one point in time is cross-sectional, so that could definitely include focus groups. In practice, nearly all focus group research is cross-sectional, because repeated waves of focus groups are quite rare.

Two good books on content analysis are those by Krippendorff and Neuendorf.

episodic memory associations can be encoded and retrieved in a context-sensitive way; thus it can be evidenced.

I use multi modal discourse analysis combined with critical perspectives from media studies. For detailed information See thesis: https://tspace.library.utoronto.ca/handle/1807/43644

For more of an over view see:

or: DOI:

I can recommend MAXQDA. In the 2022 version they have included a TeamCloud option which can be purchased as an add-on-module.

A classic one that engages with this question is:

"Microcelebrity, Self-Branding, and the Internet" from Alice Marwick (2007)

I strongly agree with the advice to emphasize your research design and how it will meet your research goals.

With regard to whether the content analytic portion of your design is interpretive, a lot depends on the extent to which you use a deductively oriented system that you generated prior to coding the data, versus an inductive system that you developed during the coding process itself.

Mixed methods requires two sets of results, one qualitative and one quantitative, as well as the integration of the those sets of results. A straightforward content analysis such as you propose would not meet this definition.

Instead, it sounds like you want to do a quantitative content analysis (i.e., based on counting things), but you want this analysis to be essentially descriptive (i.e., you will not be testing any hypotheses).

I have used MAXQDA. It is pretty user-friendly.

Hi Khalid for inter-coder reliability test, there are different formulas to use, like Scott's Pi, Krippendorff's alpha, Holsti's coefficient and Cohen's kappa. I recommend an online content analysis platform DiVoMiner® that you can do the reliability test with any of the above-mentioned formula. And there is free version if you don't have a large amount of data. Here are some video guides for every step: https://www.divominer.com/en/blog/2022/07/07/the-six-key-functions-of-divominer-2/

thank you very much

It depends on what you are trying to focus on. If you are more concerned of the bigger picture, then include the abortion debate, although in a narrower sense. If you will focus on the legal technicalities of the ruling or just the case itself, it is probably best to focus on the Roe vs. Wade literature.

It's good program

You may also find this Database of Variables for Content Analysis helpful: https://www.hope.uzh.ch/doca

Thanks Peter, this is really helpful.

لابد اولا من الاستناد الى نظرية محددة مع استخدام استمارة تحليل مضمون ترتبط بنوعية البحث ومن ثم لابد من الاستناد الى معايير قياس احصائية واضحة

Thank you very much for this question of what content analysis tools u could use to check to (fact-check) the most current misinformation or disinformation fake news.

I am aware that there are always running cases of misinformation worldwide during this globalisation era propelled by telecommunications systems, the internet, and above all, the role of social media.

In some cases, misinformation is a cultural value, a religious principle, a national policy strategy, or a gender-specific issue. You are already tools and websites that help to list sources or qualities of misinformation (disinformation).

I suggest that you focus on the current misinformation (disinformation) activities that are trending in the war between Russia and Ukraine. This will be a very good and current area.

As you are better informed, content analysis is guided by the research topic, problem, and above all the specific objective or research questions. You need to select one or more categories of media that you intend to study (analyse) and the period involved.

How do you do the content analysis in your current research will be done in a systematic way. For example, w to conduct a content analysis do:

1. Select the content you will analyze. Based on your research question, choose the texts that you will analyze.

2. Define the units and categories of analysis.

3. Develop a set of rules for coding.

4. Code the text according to the rules

5. Analyze the results and draw conclusions.

You will draft your first report and keep revising it. Take note that misinformation can be attributed in some cases to official policies at all levels, honest mistakes, poor editing or proofreading, ignorance or functional illiteracy, prejudices or discrimination, as well as good intentions for temporary solutions.

Best regards

Wilson

Content analysis (CA) is a qualitative research method for interpreting meaning from text. CA has three approaches: Conventional, directed, and summative (see Hsieh & Shannon, 2005). As pointed out by David L Morgan, CA, directed by existing theory or literature, as in your case, is a deductive approach to qualitative analysis where you start with a theoretical framework and use data to either validate or extend that framework conceptually. You could find Mayring’s (2022) guide, referenced below, relevantly useful.

Hsieh, H.-F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. https://doi.org/10.1177/1049732305276687

Mayring, P. (2022). Qualitative content analysis: A step-by-step guide. https://uk.sagepub.com/en-gb/eur/qualitative-content-analysis/book269922

Good luck,

You can dilute a weighed small sample, with an internal standard, in a medium polarity water-miscible organic solvent. Filter to separate formed solids with a syringe filter. Use a polar column at low flow and initial temperature. Whit good quality solvents, you can quantify ethanol, isopropanol and methanol

For Social Network Analysis, its better you arrange the sample data from top influncers and then compare with yours, you can use locobuzz & talkwalker

For Digital Content, Semrush & Ahrefs is best

For Audience, Google Analytics is always preferred until you have any MMP integrated

Discourse analysis, in general, entails looking at language beyond the linguistic form to examine how it reflects and is shaped by socio-cultural values. Documentary analysis often involves critical discourse analysis. The following could serve as examples.

Jackson, D., Davison, I., & Brady, J. (2022). Institutional influences on the supervision of GP trainees: A documentary analysis. Education for Primary Care, 33(1), 13–31. https://doi.org/10.1080/14739879.2021.1888661

Li, J. (2020). Political TV documentary subtitling in China: A critical discourse analysis perspective. Perspectives, 28(4), 554–574. https://doi.org/10.1080/0907676X.2019.1609533

O’Connor, P., & Barnard, S. (2021). Problematising excellence as a legitimating discourse. In P. O’Connor & K. White (Eds.), Gender, power and higher education in a globalised world (pp. 47–69). Springer International Publishing. https://doi.org/10.1007/978-3-030-69687-0_3

Good luck,

Is your main question whether you can pole together the shorter written answers you ave got with the transcribed intervviews into one data set and analyse them as a whole? My answer to this is yes you can do that.

Or is your question which method for analysis that could be used for your kind of data? My answer to that would be that a thematic analysis for example by Braun & Clarke (2006) or content analysis for example Krippendorff (2019) or Lindgren Lundman & Graneheim (2020)

Sachin, In case it's useful, a free online tool that I often use and recommend is Deen Freelon's ReCal for two coders and ReCal3 if you have three or more coders. Here is the link:

ATLAS.ti provides you with a free trial version - https://atlasti.com/free-trial-version/

we highlight that mechanistic and interpretative measures can be captured using the same content analysis instrument

Basically, content analysis depends on the number of words, sentences etc., attributed to a specific variable. In your case you can construct an index of CSP by weighing the indicators whatever they are and calculating their percentage and preparing a final composite index for regression analysis. You can consider these studies for such type of index construction:

1. It is not clear what do you mean by different studies.

2. What do you want to achieve/ what are you looking at? What kind of data are you examining? You need to clarify your objectives- the research questions, aims, and methodology.

3. I suggest that after you are clear about the 2 steps above, then do read and understand all the kind of analysis that you have stated. Choose the most appropriate kind of analysis accordingly. Best wishes.

Dear Apon Das , I would say it depends on how well you can justify to let it out. If you have good reasons to do so and can make them clear to your reader (or reviewer), I'd say, it's absolutely fine. However, just not mentioning a name will certainly be a no-go for many reviewers.

Good luck with your project!

بالتوفيق ان شاءالله

Dear Tashi Wangchuk, thank you for asking. You may try below link

Please send it to analysis it in the SPSS IBM 28 0. 0. 0 (190) version.

Josh Dyer

The simple random sample procedure and a big sample size must be created in order to minimise sampling error. The standard deviation. The sample size may then be approximated by, Sample Size Required = (z-score or t-value) 1 * StdDev*(2 * StdDev) / (margin of error) 2

To build one week from a population of one month, for example, choose one Sunday from all four Sundays that month, one Monday from all four Mondays, and so on, until each day of the week is represented in the final sample.

I think all of the qualitative software analysis packages ultimately do about the same thing, but I do prefer the way MAXQDA implements these features, as well as the quality of their tutorials and written support materials.

Hi Abdelhafid Jabri , you could borrow appraoches from the social sciences (which are usually not applied to literary works but rather newspaper articles or interview data).

You could either pick methods of qualitative content analysis, where you would develop a coding sheme based on your philosophical theory and then fine-tune it inductively on your data, see, e.g.,

Software, that supports you nicely for such endevors would be MAXQDA or NVivo.

Or, if you want to treat your theory as relatively fixed, you test it in a purely deductive way and thus develop the coding scheme completely beforehand based on your theory and then apply quantitative content analysis to your novels.

This here is the go-to introduction to the quantitative approach:

Software supporting such an approach are the 'classical' statistics tools such as SPSS (or it's free dupe PSPP), STATA or R (if you want to go pro and start programming for your project).

Here's a nice example, where R was applied to analyzing not novels with philosophical theory but at least philosophical texts themselves. It might give you a good idea of what is possible with R:

Anyway, good luck with your project!

If it is a qualitative study and focus is exploratory, then an N<50 would work.

Thank you very much

Thank you very much for your help.

Dear Geronimo Perazzo

Basically, The most common technique for determining the water content of a sample is Karl Fischer titration. The iodine is mechanically added to the alcohol solvent in the titration cell containing the sample in the volumetric method. When the iodine reaction stops, the titration has reached its end point.

Have a look: https://www.news-medical.net/life-sciences/Volumetric-Karl-Fischer-Titration.aspx

Best Regards

I have not seen this particular combination before, but without actual quantitative data, it would be hard to call this mixed methods. The alternative are either multi-methods or multiple methods.

Hi. This might give you some insights on Qualitative Research drsign although my focus is in Social Science. https://www.weijournals.com/index.php/WEJSS/article/view/22

I recommend NVivo software.

In general, there is a division between more deductive and inductive approaches to qualitative analysis, with some versions of content analysis falling on either side of this divide. The deductive approach generally involves developing a predetermined codebook and often relies on counts of codes. The inductive approach develops the codes from the data during the analysis process and is more interpretive (this would include Mayring).

Probably the most commonly used approach to inductive qualitative analysis is Braun and Clarke's (2006) Thematic Analysis. It has over 100,000 citations on Google Scholar.