Manual and computer assisted content analysis essay example

Manual content data analysis refers to physical recording and interpretation of raw research materials that have been acquired from the field through research. Contrary to this, computer assisted content data analysis is the use of computer designed software and programs to record and interpret raw information obtained from the field through scientific research.
Manual and computer assisted analysis are similar in various ways. For instance, both manual and computer assisted text analysis require well trained experts and professionals to perform. Manual data analysts have to undergo rigorous data entry and analysis training before they can commence any such duties. Similarly, computer assisted analysis largely depends on the manual input of human being at the initial stages. Automation is only possible after the raw data has been manually fed into such systems.
Manual and computer assisted content data analysis differ in some aspects. To begin with, computer aided analysis is more efficient, less tiresome, easy to distribute and store, portability, technology, expensive, less time consuming. In fact, it is referred to as automatic coding of texts and words following a specific categorization scheme. On the other hand, manual content analysis is done through hand-operated and thus done manually without any machinery or technological. This consumes a lot of time and timely analysis of such large volumes of data becomes unachievable.
Manual content analysis is complex and time consuming than computer assisted content analysis. There are a lot of manual data entries that are bent on making many references and consultations. This can thus lead to the committing of numerous errors since there are a lot of human activities that are accompanied with such analysis. On the other hand, computer assisted content analysis is less complex and is fairly straight forward.
Computer aided content analysis of data have several advantages. Just but to mention a few, this method of content data analysis is best suited for handling bulky contextual analysis. Human beings can easily get exhausted is they required to work on large documents within a slim time frame. In addition, automatic coding provides for pre-test analysis of the contents of the data to be analyzed so as to ensure that the final results are credible and reliable. This also gives rooms for more corrections and modifications on such data. The second advantage is that today there are several machines that can generate electronic text document hence making such analysis possible.
Disadvantages of computer assisted content analysis cannot be underestimated. Firstly, the coding of words is performed without putting into consideration the context in which they occur. This can lead to very wrong analysis in which the sources of such are hard to trace. Alexa reiterates that computer assisted analysis will thus uses words like bit, kind and so on to eliminate any ambiguity that may be evident in these analysis. Secondly, computer assisted analysis can best analyze texts which are relatively morphologically and grammatically restricted. This is because the softwares that are used for this automatic content analysis are designed in such a way that they can only recognize such words. This implies that data fed into such systems in languages that differ from the ones in their commanding systems will and can never be automatically analyzed and processed. Alexa echoes that this system has failed to recognize natural languages in its analysis.
In conclusion, manual and automatic or computer assisted analysis of contextual data are similar and diverse in several ways. However, recent researches have revealed that these two methods are almost fusing into one thing. These differences are in the normal sense fading off. Computers cannot work on their own without command from human beings. Besides, the data that is analyzed in this way must first be fed into the computer’s processing system manually by human beings.

Reference

Alexa, M. (1997). Ccomputer Text Analysis Methodology in the Social Sciences.
ZUMA Arbeitsbericht .