Short Samples

This example shows how T-LAB can be used for sentiment analysis tasks like classifying short texts (e.g. tweets, movie reviews, etc.) according to their opinion polarity, i.e. as ‘negative’, ‘positive’ or ‘neutral’. However the same logic can be applied to other cases of top-down (i.e. supervised) classification which use two or more categories. ...

All the Chinese articles are congregated and saved as CSV file (Fig 1), which is then input into T-LAB for corpus building (Fig 2). Articles are distinguished by ID numbers and type of newspaper (i.e. print vs online).
The above CSV file with each article at a row can be input into T-LAB and further be segmented and lemmatized.
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This example will show a textual analysis that was performed on the open-ended questions of the Survey about T-LAB and Text Analysis Software. The survey was conducted by a research team at the Catholic University of Milan (Italy) and aimed to analyse the user experience of T-LAB and other software for text analysis. It also aimed to compare the perceived image of T-LAB to that of its main competitors. ...

On June 23rd 2016 the people of the UK decided to 'leave' the European Union. The causes and the consequences of this event will be discussed for decades.

This short example consists of a sort of exercise through which, while analysing a popular book of the sociologist Anthony Giddens (i.e. The Politics of Climate Change), we focus on methodological issues concerning the use of some T-LAB tools for text analysis.

    www.tlab.it Exploring US Presidential Inaugural Addresses A piece of whimsy about text and context (7 February 2009. The version of T-LAB used was T-LAB […]