Detecting emotional polarity in F innish parliamentary proceedings (2024)

Abstract: Few studies have focused on detecting emotion in parliamentary corpora, and none have done this for the Finnish parliament. In this paper, this gap is addressed by applying the polarity lexicon–based methodology of a study by Rheault et al. (2016) on speeches in the British Parliament to a Finnish corpus. The findings show an increase in positive sentiment over time. Additionally, the findings indicate that politicians’ emotional states may be impacted by the state of the economy and other major events, such as the Covid-19 pandemic and the Russian invasion of Ukraine.

## introduction 1.goal the goal of this paper is to apply the methodology used by @xcite on british parliamentary speeches to a finnish dataset, in order to determine whether the findings -increase in emotional polarity over time and correlation with the state of the economy -can be replicated with a different corpus in another language. additionally, comparison to other major events, namely the covid-19 pandemic and the russian invasion of ukraine, is drawn in order to investigate which other topics may impact emotional polarity. ## conclusion the results broadly align with those shown by @xcite , with an increase in positive sentiment over time, and correlation between polarity and certain economic measures. however, this correlation could only be seen with certain measures, and the measures involved were slightly different between this study and rheault et al. links between labour disputes and polarity and the misery index and polarity could not be demonstrated. further investigation into the topic is needed in order to conclusively determine whether economic measures impact the emotion shown in parliamentary speech. one future avenue of research that would likely prove fruitful is sentiment analysis through a machine learning approach, as this can achieve a higher accuracy compared to polarity lexicon-based methods, although at the expense of interpretability @xcite . additionally, utilising contextual word embedding methods such as elmo @xcite or bert @xcite would be worthwhile, as these may perform better compared to older word embedding methods such as glove @xcite . some correlation was also seen between the other studied events and emotional polarity. further evaluation could determine whether this can be explained by words related to these events being evaluated as negative, or whether discussions unrelated to these topics also show a lowered polarity. future study could classify speeches by topic, a task which has already been performed with finnish parliamentary data @xcite , and eliminate speeches related to the events in question, in order to only focus on the unrelated speeches.