On the 3rd of February, 2017 our company had the honor of participating in the 11th Conference for PhD Students of Applied Linguistics not with one, neither with two, but with three presentations. Martina Szabó, our colleague has recently finished her PhD studies at the University of Szeged in applied linguistics and led multiple researches with our NLP team on the field of Hungarian emotion and sentiment analysis.

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Martina, Gergő, Berni and Zsófi

    We presented our findings in three articles: Martina Szabó and Fanni Drávucz wrote about the problem of subjectivity in connection with emotions and sentiments. They were looking for the linguistic signs of uncertainty in our emotion and sentiment corpus and they found that in the emotion corpus there are 2.5 times more linguistic signs of uncertainty, which proves that they are indeed more personal and subjective than sentiments. They also found that the negative emotions and the negative sentiment are more closely connected to uncertainty, which could arise from the more polite and indirect expressing of such emotions or opinions.

    The second article were based on a research where we collected and analyzed a corpus of Hungarian tweets, looking for polarity-changing elements. These lexically negative linguistic items can lose or change their polarity and bear a positive or neutral value as an intensifier. In their research, Martina Szabó, Zsófi Nyíri, Bernadett Lázár and Gergő Morvay analyzed the usage of such intensifiers by male and female Twitter-users, and found that while female users preferred to use them connected to negative adjectives, male users used them more often with positive or negative adjectives and had an overall preference to swear words.

    In an other research, Martina Szabó, Zsófi Nyíri and Bernadett Lázár examined the translatability of negative intensifiers from Russian to English. These linguistic elements are so delicate and complex that their complete meaning is often lost in translation. They analyzed a Russian-English corpus with parallel texts and found that such intensifiers in Russian are often translated into English with a neutral intensifier, partly losing the original meaning, but there is a difference in interpreting negative intensifiers in connection with negative or positive adjectives.

We are really proud of Martina and our NLP team for such a hard work!

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