The output option Summary in the Query search is one of the three main functions of automatic content analysis in AmCAT. The Summary function is very useful to get a first impression of the content of the debate concerning your topics of interest in the documents.
The Summary function provides the possibility to show all articles from the selected article set(s) that contain one or more of the search terms you entered in the 'Keyword Search string(s)' field. When you select 'Summary' and click on the 'Submit' button below the output options, AmCAT provides you with the number of articles in which one or multiple of your search terms occur, followed by a list of all these documents under 'Found # articles'. Of each article, a number of characteristics is displayed: the title of the article, the date, the number of words, the medium and the context in which your search terms were mentioned in the text (with your search terms displayed in red). Figure 5.1 shows an example of the Summary function with the search terms "obama OR terrorism". As you can see, a total of 541 articles was found including one of these search terms. The first article in the list was published at June 6, 2006 and mentions the word terrorism at least three times (as this word is displayed in red three times in the article preview). When you click on the title of an article in this list, AmCAT shows you the full text article, with the included search terms highlighted in yellow, and some additional article details.
The Summary function has four additional possibilities: Assign as codingjob, ClusterMap, Associations and Save as Set (see Figure 5.1 upper right corner). Each of these possibilities is discussed below.
The Summary Assign as codingjob function will save the documents that were found in the article set using your search string as a new article set and will create a codingjob at the same time. To do so, you name the new article set, assign a coder to the codingjob, and select the unitschema and articleschema (see Figure 5.2).
The Summary ClusterMap function provides you with the possibility to create a venn diagram showing the overlap between different search strings. In order to be able to create a venn diagram, you need to enter at least two different search strings in the 'Keyword Search string(s)' field. A venn diagram is useful for the visualization of the extent to which different concepts are related to one another. In other words, a venn diagram presents associative frames.
Select ClusterMap, select 'Show in navigator' and click 'Ok'. AmCAT now displays a venn diagram with the conceptual overlap of your search strings. When you have a relatively small number of articles, the venn diagram displays little dots within larger colored shapes. These dots represent particular articles in the article set. When you click on one of these dots you will see the particular article in which your concepts overlap. If you have a relativey large number of articles, the venn digram displays a single large dot.
If we want to measure how often terrorism is related to either Israel or Palestine, for example, we can enter (1) Terrorism#terror*, (2) Israel#israel* and (3) Palestine#palesti* in the 'Keyword Search string(s)' field. Please note that each of these search terms started at a new line. Figure 5.3 shows this particular venn diagram. A total of 1190 articles was found. You can see that the majority of these articles (1016 articles) do not associate terrorism with either Palestine or Israel. Moreover, you can see that only two articles were found in which Palestine was mentioned, but not in combination with terrorism of Israel. Ninety articles mentioned all three concepts together. Below the venn diagram, AmCAT shows a table with the exact number of articles that mention your search terms, either alone or combined with (another) search term(s). Note that '0' indicated that the concept is not mentioned in the article and that '1' indicates that a concept is mentioned in the article).
When you select one of the other formats as the output of the ClusterMap rather than 'Show in navigator', either CSV, Excel or SPSS, you can save the quantitative data on which the venn diagram is based in another format and open and process the data in another program. The CSV file contains a datamatrix which shows, for each combination of your search strings, how often a particular combination occurs.
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