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Short Samples:
BIOTECH AND GENETICALLY MODIFIED ORGANISMS
(Last update: May 3th, 2003. The version of T-LAB used was 3.0)

NOTICE: The following example has been realized by using an old version of T-LAB (3.0). The latest version (T-LAB 7.0) includes new tools and a new charting system.
Click here to find out more.

T-LAB functions used in this short example are those highlighted in red in the image on the right.

For futher information about T-LAB functions click here.

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In the corpus we have put together around 200 short articles, concerning the biotech and genetically modified organisms, published in 1999 on London daily newspapers.

The Co-Word Mapping option automatically produces the following map.
(N.B.: Starting from 5.0 version, the Co-Word Mapping tool is no more available. Its functionalities are now included in the Co-Word Analysis and Concept Mapping tool.)

 

 

 

 

In the map, each box is marked by a key-word, the most frequent among a small subset of other words that occur with it in the same sentences (co-occurrences) .
In statistical terms, the bi-dimesional space come of the first two factors extracted by correspondence analysis.

For each subset it is possible to identify the elements that form it. See the following samples, obtained by a click on the corresponding labels.

CUNNINGHAM
RESEARCH
PESTICIDE
SUPERMARKET

To help interpret the map, T-LAB automatically produces tables showing the words characteristic of the (-) and (+) polarities, or of the left-right, high-low contrasts.

 

Description of the orizontal axis.

As you can see,

- on left-hand pole (-) are grouped the words concerning the POLITICAL RAMIFICATIONS;

- the right-hand pole (+) consists of the words concerning the FOOD INDUSTRY.

 

 

Description of the vertical axis.

As you can see,

- on low-hand pole (-) are grouped the words touching the FOOD SAFETY CONCERNS;

- the high-hand pole (+) consists of the words concerning the relationships between MARKET AND CONSUMER.

Therefore the main topics of articles turn out organized in the following way:

 

A further T-LAB option (Associations) allows us to explore the local meanings of each key-word.
In fact this option shows the words in the corpus that share co-occurrence contexts with each selected key-term.
In the graphs, the selected words are placed in the center. The others are distributed around it, each at distance proportional to its degree of association. The significant relationships are therefore one-to-one, to the central word and to each of the others.

For each graph, a table shows the data used to create it.
Column by column the reading keys are as follows:
- LEMMA_B = lemmas associated whit "central" lemma (or LEMMA_A; see "biotech");
- COEFF = cosine coefficients;
- OCC_B = occurrences of each LEMMA_B;
- ASSOC_AB = co-occurrences of lemmas "A" and " B ".