Content Analysis in Social Research

An Overview Description of the Content Analysis

Content analysis is a research tool applied mainly in qualitative analysis to identify the presence of certain concepts, themes, and words within qualitative data. A researcher can use content analysis to analyze and quantify meanings and the connections that the pieces and phrases have in the qualitative data. For instance, a researcher can use a content analysis tool to examine the language used in a news article to identify the presence of biases (Bengtsson, 2016). The researcher can collect data from open-ended questions, interviews, books, other literature, discussions, and field research when working with this research tool. The analysis process begins with breaking down the content into manageable codes, which is referred to as coding. The coded information is then categorized, then a further summary is done

It is also essential to understand that content analysis is unique, mainly because it has a qualitative and quantitative methodology. At the same time, it can be used in an inductive and deductive way. The origin of quantitative content analysis is media research, but qualitative content analysis originated from social research. Even though these methods are as described, none of them has a connection to any form of science (Schreirer, 2012). This being the case, this method lacks a specific concept, and any ideas used are universal. Another notable fact about this data analysis method is that when points are taken from a text, they are presented as frequencies expressed in percentages or in the form of numbers for critical categories in quantitative content analysis. The quantitative content analysis method summarises details regarding a message instead of reporting it in full (Bengtsson, 2016).

On the other hand, qualitative content analysis proposes the representation of data in words and themes, which has an advantage because it makes the interpretation of results easier. The choice of analysis method is dependent on the depth of the analysis that the researcher attempts to reflect on the information offered by an informant. This has a ripple effect because it affects the number of informants needed and how data is collected. Thus, the researcher must select whether the analysis must be manifest or latent. In an axiomatic analysis, the informant says the information in the text and the text word for word. In many cases, they describe what is visible in the text. The contrast latent analysis uses an interpretive level of analysis where the researcher extends to an interpretive level in which the researcher seeks to deduce the inner meaning of a text.

Putting Content Analysis into Practice

When using this research approach, the researcher does their best to avoid preconceived categories, and thus, the names of the classes proceeded from the data. Also, when using this approach, the researcher gets deeper into the data, which allows them to get new insights, also described as inductive category development. Many qualitative methods share this first method of study design and analysis (Schreier, 2012). The nature of that data transmits the data collected by a researcher when using content analysis, whether verbal or non-verbal interaction. It is essential for the verbal or non-verbal questions to adapt to the claim of the referenced method. When this happens, the researcher will find some form of understanding of the phenomenon under study. All the questions connected to the study’s objectives can be employed at the same time as content analysis. Therefore, the researcher is faced with a scenario where they are never confident that the method used in data collection can provide data that gives the real context of the informants.

It is essential to realize that the words the informants use may not be similar to the meaning made by the researcher. Some misinterpretations may arise when the informants fail to give the entire truth in cases where they fail to express themselves or when they are affected by what they believe the researchers demand. Data collected through the interviews, discussions, and focus groups are recorded in video or audio format. These recordings are usually transcribed into written forms, which is an interpretive process. Thus, when this information is transcribed, it should take note of the tone, emphasis, speed, and timing. These components sometimes cannot be written and captured. It is preferred that the researcher should do a transcription.

Hence if researchers collect data using interviews alone, they will employ the open-ended questions approach. It is essential to understand that probes are also open-ended, and the response is unique to the specific participant. This is different from a pre-existing theory, like in the case where one asks the question, “Please tell me more about it?” In such a case, data analysis will begin by reading all the data again and again to achieve immersion and eventually obtain a sense of a whole, like a person reading a novel (Moretti et al., 2011). Next, the researcher reads the data word for word as they derive the codes. This process is done by first highlighting the exact words from the texts that seem to capture the key concepts. Then, the researcher makes notes from the text based on their first ideas, impressions, and initial analysis. While this process is going on, the labels for codes will emerge automatically. These labels emerge so that they offer more than one idea. These ideas come directly from the texts, and they become the initial coding scheme for the researcher (Moretti et al., 2011).

The codes are then stored in categories based on the connections between the principles. Then, the emerging classes are used to organize the codes into meaningful groups. The clusters should be between ten and fifteen so that the collection is broad enough to sort a larger number. The one striking thing is that when using content analysis, a single study can be used to analyze different forms of texts within that single analysis. Bengtsson (2016) says that three definitions can be used to describe content analysis. The first definition is a technique used to identify unique features in a message systematically. In addition, it can be a method used to make inferences by systematically identifying special features in a text. It can also systematically and objectively describe the contents manifested in communication.

A Detailed Content Analysis

This content analysis was a study on viral videos, and the intention is to provide quantitative data showing the dominant factor in viral videos on social media. Videos were sampled and compiled through the visible measure. The selected videos were published weekly and listed as the top 10. Three factors determined the weight of the videos. 1) Video placement, 2) views of the video, and 3) sentient analysis. Notably, video placements are the seeded and viral placement of the videos. Video views are the number of times a video was viewed, and sentiment analysis is the social media responses to the video. Every week, the videos were ranked between December 23^rd, 2018, and December 2021. Within this time, 108 videos were ranked for 101 weeks. While several videos appeared severally on the charts, they were only coded once.

The coding procedure employed two codes where the sampled list of videos was sampled. A codebook was created that clearly defined every point aligned to the coding sheet. The coding was done using an online database that gave each coder a unique user ID. The testing sample was made of 26 viral advertisement videos that were coded and tested for reliability using Holsti’s method. The inter-coder reliability showed that scores were within the acceptable range of >.85. This was after the training: the level of involvement scored .73, and the strategies scored .68.

Inter-Coder Reliability

Category	Holtsi’s score
Brand appearance	1.0
Country of Origin	1.0
Product Category	1.0
Advertising appeal	1.0
Pricing Product	1.0
Level of Involvement	.86
Television formatting Frame	.95
Messaging strategy	.89

During this content analysis of advertisement videos from social media, four areas were identified for measurement. These were technical factors, the message in the video, the advertising characteristics, and the video involvement of the product in every viral advertisement video (Bengtsson, 2016). The measured technical factors were selected such that they could reveal the commonalities between the online videos. The areas recorded to evaluate the technical factors were the title of the video, the length of the video, the URL, the date posted, and the video formatting frame. The other factors that were considered when examining the commonalities were the presenter, demonstration, straight announcement, true testimonials, musical commercials, and the inclusion of graphics.

The messaging content was also analyzed in every video. Three areas were examined: the messaging strategy, the marketing appeal, and product pricing. This messaging strategy was categorized based on Taylor’s six-phase wheel. The coder was set to evaluate the advertisements based on the dominance of the messaging system: the acute needs, rational needs, sensory appalls, and consumer ego (Babbie, 2007). The other messaging category assessed sex appeal, information, humor, adventure, and emotional action. The researcher sought to examine the commonly used appeals in the marketing videos. The last messaging category that was also evaluated was the role of product pricing in the viral advertisement video. This category was measured to examine the significance of the video when it was later paralleled with the involvement level.

The third section of the coding targeted the advertiser characteristics. These characteristics were based on the core content used to make the videos. The marketing film agency that created the brand, the brand itself, and the country of origin were among the key categories. The other categories considered were the product type if the brand was mentioned, and when the brand was mentioned (Levitt et al., 2017). These categories were then selected to help the researcher identify some common features of these adverts, like which companies have the leading track records in creating viral advertisements. These categories also helped identify the common techniques used by these marketing agencies. Identifying and determining the dominant features of the video helps the companies create new campaign videos so that the case studies of the previous successes are reviewed to make better videos (Schreirer, 2012).

The researcher’s interest is to measure the product categories and the frequency of the appearance of each product category in the sampled videos. The connection between the level of involvement and the product category was made, and a comparison was made to determine advertisement appeal. The last measure was product involvement. There was only one question featured in this category: the level of participation that the advert demanded from the audience or consumers. The coder was set to select one of the following options: high involvement, low emotional involvement, rational-high involvement, rational and low involvement, and emotional involvement. The results of the research were as follows;

Country of Origin

Country	Number of instances	Percentage
United States	210	80%
United Kingdom	35	12%
Other Countries	23	8%

Brand Appearance

Period of appearance	Number of instances	Percentage
First Third	170	63%
Second Third	10	4%
Final Third	85	30%
Not at all	5	3%

Formatting Frame

Types of Frames Used	Number of instances	Percentage
Slice of Life	65	24%
Demonstration	58	21%
Musical Commercial	47	17%
Lifestyle	43	16%
True Testimony	20	7%
Straight Announcer	16	5%
Presenter	11	4%
Computer Graphics	8	5%
Other	2	1%

Messaging Strategy

Strategy Category	Number of Instances	Percentages
Routine	86	31%
Sensory appeal	82	30%
Ego	60	22%
Rational	22	8%
Social needs	16	5%
Acute Needs	3	4%

Advertising Appeal

Appeals	Number of instances	Percentage
Humour	170	63%
Sex appeal	30	4%
Other	70	30%
	12	3%

Level of Involvement

Level of involvement	Was product pricing utilized?   YES                            NO		Total
High Involvement Rational	3	78	81
High Involvement Emotional	0	17	17
Low Involvement Rational	5	51	56
Low Involvement Emotional	8	109	117
Total	16	255	271

 

Gaps in Literature and Recommendations

This study conducted by content analysis revealed a familiar pattern among viral videos on social media, and marketers can use that in the future. There was also a notable fact that the process was repetitive and seemed easier to reproduce (Babbie, 2007). The companies that produced viral videos on social media also produced failed videos. Still, this study managed to reveal how social media video content can be used to gauge the popularity or lack of popularity of viral videos. The content analysis study focused on the components that make up a viral video but did not place any emphasis or interest on the networks used to spread these videos. Viral videos are like viruses, and hence, they need a medium to spread across the internet. The social sharing of viral videos is made possible through social media like Facebook, Twitter, and even YouTube. The gap that remains is the study of social media sites to reveal which social media sites are best suited to spread the videos. Also, the study did not examine users of these videos. Yet, there are indicators that a study in that area can offer the revelation of certain video components that can cause a higher rate of visibility.

It is recommended that the communal nature of sharing viral videos should be studied further in the future. Also, a study of online users should be done to offer insight into the economic data. The most outstanding limitation is that even though the study of the creation and implementation of viral videos is useful, it is essential to know that there is no guarantee of how the public will perceive any viral advertisement video. However, they still offer some insight into marketing and reveal the significant impact that content analysis can play in illuminating dominant themes.

References

Babbie, E.  (2007).The Practice of Social Research. CA: Wadsworth Publishers, Belmont.

Bengtsson, M. (2016). How to plan and perform a qualitative study using content analysis. NursingPlus Open, 2, 8-14. https://doi.org/10.1016/j.npls.2016.01.001

Levitt, Heidi M.; Motulsky, Sue L.; Wertz, Fredrick J.; Morrow, Susan L. & Ponterotto, Joseph G. (2017). Recommendations for designing and reviewing qualitative research in psychology: Promoting methodological integrity. Qualitative Psychology, 4(1), 2-   22.

Moretti,  F.,  Fan Vliet,  L.,  Bensing, J.,  Deledda,  G., Mazzi,  M., Rimondini,  M., Zimmermann,  C.,  and  Fletcher,  I.  (2011). A standardized approach to qualitative content analysis of focus group discussions from different countries. Patient Education and Counselling, 82(3), 420-428

Schreirer, M.  (2012)  Qualitative Content Analysis in Practice: CA: Sage Publishers. Thousand Oaks

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For this second assignment, construct a 7-9 page paper that:

a) illustrates an accurate description of content analysis as it applies to qualitative methods supported by classroom concepts;

b) provides a detailed content analysis (with matrix) of a particular form of popular media (via either 30-plus minutes of content, 20-25 images, or some other parameter (instructor permission for which must have been obtained prior to the submission of this assignment); and

c) Identify extant gaps in the literature and recommend further research in the content analysis area based on the findings of your analysis.

Make sure that you clearly indicate if your approach is relational or conceptual. Regardless of the type of content method you choose, make sure that you mention possible patterns or themes in your essay. Last, content analysis is often triangulated with other methods. When you address extant gaps in the literature and recommendations for future research, you should posit a complementary method of inferential testing for content analysis and your media selection.

Your paper should utilize sound critical thought, refer to course materials, and be written in APA format as per the 7th Ed. (to include a title page, abstract, appropriate in-text citations, and a reference page).

For help with APA formatting, consult the APA manual (2019) and/or the following websites:

https://apastyle.apa.org/

https://www.scribbr.com/apa-style/apa-seventh-edition-changes/

https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_format.html

For Additional assistance creating a matrix, consult the following:

https://www.betterevaluation.org/en/evaluation-options/framework_matrices

https://www.scribbr.com/methodology/content-analysis/