|This page describes a feature in AmCAT 3.3|
|View other version: 3.3 - 3.4 - 3.5|
An AmCAT project starts in the AmCAT Navigator. Open your browser (e.g., Firefox, Google Chrome or Internet Explorer), go to https://amcat.nl and log in to AmCAT. In order to be able to log in, you need to create an account.
Logging in brings you to the AmCAT home page, where you can access and manage your AmCAT projects by clicking on the 'Manage Projects' button. This directs you to the location where your AmCAT projects are stored. These can be your own projects or the projects of other AmCAT users that allow you to take on a guest role. You can choose to list either your 'Active Projects', your 'Archived Projects' or 'All Projects' (including those that you are not a member of) by clicking on these tabs. AmCAT displays your active projects by default, listing all the AmCAT projects you are currently working on. This list is empty for a new user, but you can easily create a new AmCAT project.
If you want to start a new AmCAT project, the first step is to create a new AmCAT project and to upload articles to this project. When the AmCAT project has been created and articles have been uploaded, you select the relevant project by clicking on the project name. Selecting a project brings you to the article sets (i.e. collections of texts) this particular project contains. You can use each of your article sets separately or (selections of them) all together. On the AmCAT home page you can also find a number of featured article sets you can use.
As an example, we use an article set called ‘nyc nuclear* or atom* in lead', an article set with all New York Times articles that have one or more words starting with ‘nuclear’ or ‘atom’ in their lead paragraph, from the years 1946 to 2013. As you can see in the Figure above, this article set includes 58036 articles. By clicking on the article set you will get an overview of all articles in this set (see the Figure below). The overview shows you various metadata for each article, such as the (article)id, date, headline, mediumid, medium and length (in words) of each article in the article set. Clicking on an article in the table shows you the full article text.
When you are familiar with the type of data you are dealing with, you can start your automatic or manual content analysis by querying your article sets or creating resources for manual annotation. You perform your automatic content analysis using the AmCAT Query Search function. After selecting an article set you get the overview of all the articles. In the upper left corner you find a blue 'Query' button. Click on this button and you get the AmCAT Query search screen. Here you select media and time periods of the articles you want to include in your analysis and, if applicable, save this selection of specific articles as a new article set. You start your automatic content analysis by creating search strings (i.e. a combination of search terms) and entering them in the 'Keyword Search string(s)' field. You enter all the search terms covering what you perceive as being one topic on one row in this field. You can also enter multiple search strings in this field at the same time (if you want to compare different topics, for example) by starting each search string at a new row. The length of your search strings is unlimited. Please note that the quality of your automatic content analysis depends on the quality of your search strings, which in turn depends on the reliability of your search strings. Hence, it is very important to test the reliability of your search strings.
The AmCAT Query search has various functions you can use to analyse your data. Among the 'Output options' you find summary, article list, graph/table and Network output options, each representing a main function of automatic content analysis in AmCAT.
You can test various hypotheses using content analysis. You can extrapolate your findings (i.e. generalization them to a broader context, which you have not actually measured). Examples of such extrapolations are trends, patterns and differences. From these trends, patterns and differences you observe in the collection of documents that you analyzed (your sample), you can draw conclusions about similar documents that you have not actually analyzed (the population) and thus test your hypotheses.