How to measure Twitter content polarity

The European Commission’s EMPL presence on Twitter in 2012: Positivity index

Scholars advise identifying the emotional value that is carried by the content itself while doing a content analysis. In the context of this research project, I thought that applying and calculating the Losada Line (also called Losada Ratio) would enhance the results and provide additional insights on communication patterns developed by the research subjects, namely Social EuropeEURes and Commissioner Andor in 2012.

Figure 1: Positivity index analytics based on Losada Line

Figure 1: Positivity index analytics based on Losada Line

The Losada Line is a visual representation of a scale where the values reflect the positive and negative dimensions of a written or an oral speech. The critical point is 2.9, which resulted according to a complex algorithm developed by Marcial F. Losada. A ratio of 3.0 to 6.0 on the Losada Line is the optimal range that reflects a normal positivity index. The index is calculated by dividing the ratio of positive emotions (posemo) by the ratio of negative emotions (negemo). Both “posemo” and “negemo” are two LIWC output values presented in Table 1 in this article.

The positivity index is as follows: 4,14 for Social Europe, 7,12 for EURes and 4,01 for Commissioner Andor while the average user ratio is 4,32, which is optimal (Figure 1). According to Losada Line algorithm, Social Europe and Commissioner Andor produced content with a normal positivity index while EURes appeared too positive, being placed at above 6.0 (7,12). According to Tausczik and Pennebaker[1] (2010), “assents and positive emotion words measure levels of agreement” (p. 32).


[1] Tausczik, Y. R. and Pennebaker J. W. (2010), “The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods”, in Journal of Language and Social Psychology, 29 (I) 24-54, Sage Publications

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