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Elementary Content Analysis of the Internet Pages

Main interests revolve around blockchain technology, coding, and artificial intelligence.


Posted 3 months ago on August 4th, 2021. Last modified on September 28th, 2021

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It is always a smart idea to check what your competitors are doing online. Even if you are just starting your page as an enthusiast, conducting an online content analysis can give you a good idea of what works, and what doesn’t. We will tell you what it is and how to go about it.

When defining content analysis, it can be said to be a method of research used to identify certain patterns in a set of data. Typically, the data consists of text, whether it be visual, written, or oral. Some examples where such research is applied would be magazines, books, interviews, movies, social media posts, and various web content.

There are two main approaches to content analysis. The quantitative approach focuses on measuring and counting sets of data. The qualitative approach deals with a focus on understanding and interpreting text. Both share the same methodology, namely coding words. Codes can be categorized in regard to certain concepts, words, or themes in a text.

Once the coding is done, the results get analyzed. Content analysis as a method of data collection is popular amongst businesses, especially when it comes to doing digital marketing research. You can rest assured that your favorite brands, companies, and the best uk casinos all take advantage of this efficient way to analyze the web.

What Does Content Analysis Get Used for?

Content analysis allows researchers to study the effects, overall message, and purpose of written content. The method gives insight into both the intended audience of the text and the intent of the producers. For one, the occurrence of particular phrases, subjects, or words can give a variety of information when considered in a specific context.

An applied quantitative content analysis example could investigate the frequency of words like work, unemployment, and jobs in the speeches of political campaigns. Over time, a statistical analysis can give a good overview of how individual candidates differ, how much they prioritize a given issue, and so forth.

Using the qualitative approach, one would pick out the reoccurring words in political speeches. Then, one would continue to analyze the relationships to the surrounding words and phrases. Say the word unemployment is surrounded by words like inequality, economy, and indifference several times. The qualitative analysis would delve into the semantic relationship of the concepts. That can give one a wholesome insight into the targets and intentions of a political campaign speech. Overall, content analysis can be used in a wide range of texts, such as cognitive science, anthropology, psychology, marketing, and media studies.

The purpose of content analysis can be manifold. It can help to seek out patterns pertaining to how certain concepts are communicated, and understand the underlying intentions of an institution, individual, or group. It is an effective method to make out propagandist biases. Content analysis can also reveal how an entity's communication differs in diverse contexts. Lastly, this research method can give insight into what consequences a given text has by analyzing the response messages of the audience. In our case, all of these purposes apply to content analysis of the internet pages because the web is vastly different in its scope.

Content Analysis - Advantages and Disadvantages

There are three main benefits of content analysis on internet pages. Firstly, it is completely unobtrusive. You can analyze social interactions, and text data without having to be a direct participant. It means that your presence as an investigator will not have an impact on the results. Secondly, website content analysis is replicable and transparent.

When following a systematic approach, the results of your research can be easily replicated by others, indicating it is a method with a high rate of reliability. Thirdly, content analysis is incredibly flexible. If you have the appropriate sources for your research, then a study can be done with little cost, anywhere, and at any time.

There are also some disadvantages to this method. Content analysis operates on a reductive approach. Sometimes this can yield results that do not fully grasp the context, possible ambiguity of meaning, or nuance in a given text. Another disadvantage is that content analysis always involves a factor of subjectivity.

Depending on the researcher, interpretations of meaning can vary, and the results may vary accordingly. That is why a highly systematic approach and reliable researchers are of significant importance. Lastly, website content analysis is quite arduous and takes a long time. The procedure is hard to automate, and thus it requires lots of effort on the side of the investigator.

Conducting a Web Page Content Analysis

At the start of your process, make sure to formulate a concise research question. An example could look like this: Does the internet media represent the trustworthiness of male and female politicians in different, biased fashions? After you have your query formulated, you can move on to the methodology.

Outline the Content That You Will Analyze

Do some research around the web and select what type of internet pages you will choose to analyze. You have to decide which media you will look at. That could be blog posts, internet news pages, marketing copy, social media, and the like. Pick a relevant genre. Continue to pick the criteria for including a web page in your research. The criteria could have to do with a topic, person, or anything else you are interested in. Lastly, set the parameters like the location, date, and circumstance.

Choose Your Categories and Units for Analysis

In the second step, you have to define what units will be coded. Units are defined by the meaning you assign to them. That means you could go for recording the characteristics of the personalities in a text, the portraying of certain themes, frequency of words, and so on. Once you have your units, continue to set your categories. Categories of research can be objective characteristics, like male, officer, kind, aged 30-35, etc. Alike characteristics such as kind, generous, open, can be coded under one umbrella such as trustworthiness.

Make Coding Rules

The act of coding is about organizing your allocated units of meaning to your defined set of categories. You have to set the rules as to what will be included in categories, and what won't. Let’s say you have a category of male politicians. If you come across a mayor, senator, and counselor, which ones will you include, which will you keep out? The same goes for characteristics, you set the rules as they are relevant to your particular research topic.

Start Coding the Texts

Once you’ve set your parameters, start your research and begin coding your web texts. Record all of your defined units, be diligent, and keep your coding parameters consistent. That is very important for your result.

Analyze Your Results, Make Conclusions

After you finish coding, move on to examining your data. Look for any patterns that you can see, then group them together. Are there any correlating trends? What interpretations are you inclined to make? What conclusions can you draw from your results? Make inferences about the texts, their creators, the audience, and the particular context of the data.

We hope that you enjoyed our overview on how to do basic content analysis on internet pages. It is fairly simple, as the system depends on what your specific research interests are. To be able to draw a strong conclusion, make sure to stay consistent in your coding practice. Do you find doing content analysis useful? For what do you use it, and how do you go about it? We would love to hear your opinions in the comments below!


About the Author: Arthur Rowley is a programming specialist from Ohio, USA. It is his passion to share his knowledge on all things related to tech with people who are keen to learn. His main interests revolve around blockchain technology, coding, and artificial intelligence.

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