Prevention or Promotion? Predicting Author's Regulatory Focus
People differ fundamentally in what motivates them to pursue a goal and how they approach it. For instance, some people seek growth and show eagerness, whereas others prefer security and are vigilant. The concept of regulatory focus is employed in psychology, to explain and predict this goal-dir...
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| Format: | Article |
| Language: | English |
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Linköping University Electronic Press
2023-09-01
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| Series: | Northern European Journal of Language Technology |
| Online Access: | https://nejlt.ep.liu.se/article/view/4561 |
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| _version_ | 1832591276819611648 |
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| author | Aswathy Velutharambath Kai Sassenberg Roman Klinger |
| author_facet | Aswathy Velutharambath Kai Sassenberg Roman Klinger |
| author_sort | Aswathy Velutharambath |
| collection | DOAJ |
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People differ fundamentally in what motivates them to pursue a goal and how they approach it. For instance, some people seek growth and show eagerness, whereas others prefer security and are vigilant. The concept of regulatory focus is employed in psychology, to explain and predict this goal-directed behavior of humans underpinned by two unique motivational systems – the promotion and the prevention system. Traditionally, text analysis methods using closed-vocabularies are employed to assess the distinctive linguistic patterns associated with the two systems. From an NLP perspective, automatically detecting the regulatory focus of individuals from text provides valuable insights into the behavioral inclinations of the author, finding its applications in areas like marketing or health communication. However, the concept never made an impactful debut in computational linguistics research. To bridge this gap we introduce the novel task of regulatory focus classification from text and present two complementary German datasets – (1) experimentally generated event descriptions and (2) manually annotated short social media texts used for evaluating the generalizability of models on real-world data. First, we conduct a correlation analysis to verify if the linguistic footprints of regulatory focus reported in psychology studies are observable and to what extent in our datasets. For automatic classification, we compare closed-vocabulary-based analyses with a state-of-the-art BERT-based text classification model and observe that the latter outperforms lexicon-based approaches on experimental data and is notably better on out-of-domain Twitter data.
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| format | Article |
| id | doaj-art-f9d163557bbc4160bac1cfb4fbf3ed9a |
| institution | Kabale University |
| issn | 2000-1533 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | Linköping University Electronic Press |
| record_format | Article |
| series | Northern European Journal of Language Technology |
| spelling | doaj-art-f9d163557bbc4160bac1cfb4fbf3ed9a2025-01-22T15:25:15ZengLinköping University Electronic PressNorthern European Journal of Language Technology2000-15332023-09-019110.3384/nejlt.2000-1533.2023.4561Prevention or Promotion? Predicting Author's Regulatory FocusAswathy Velutharambath0Kai Sassenberg1Roman Klinger2University of StuttgartLeibniz-Institut für Wissensmedien, Tübingen, Germany and University of Tübingen, GermanyUniversity of Stuttgart, Germany People differ fundamentally in what motivates them to pursue a goal and how they approach it. For instance, some people seek growth and show eagerness, whereas others prefer security and are vigilant. The concept of regulatory focus is employed in psychology, to explain and predict this goal-directed behavior of humans underpinned by two unique motivational systems – the promotion and the prevention system. Traditionally, text analysis methods using closed-vocabularies are employed to assess the distinctive linguistic patterns associated with the two systems. From an NLP perspective, automatically detecting the regulatory focus of individuals from text provides valuable insights into the behavioral inclinations of the author, finding its applications in areas like marketing or health communication. However, the concept never made an impactful debut in computational linguistics research. To bridge this gap we introduce the novel task of regulatory focus classification from text and present two complementary German datasets – (1) experimentally generated event descriptions and (2) manually annotated short social media texts used for evaluating the generalizability of models on real-world data. First, we conduct a correlation analysis to verify if the linguistic footprints of regulatory focus reported in psychology studies are observable and to what extent in our datasets. For automatic classification, we compare closed-vocabulary-based analyses with a state-of-the-art BERT-based text classification model and observe that the latter outperforms lexicon-based approaches on experimental data and is notably better on out-of-domain Twitter data. https://nejlt.ep.liu.se/article/view/4561 |
| spellingShingle | Aswathy Velutharambath Kai Sassenberg Roman Klinger Prevention or Promotion? Predicting Author's Regulatory Focus Northern European Journal of Language Technology |
| title | Prevention or Promotion? Predicting Author's Regulatory Focus |
| title_full | Prevention or Promotion? Predicting Author's Regulatory Focus |
| title_fullStr | Prevention or Promotion? Predicting Author's Regulatory Focus |
| title_full_unstemmed | Prevention or Promotion? Predicting Author's Regulatory Focus |
| title_short | Prevention or Promotion? Predicting Author's Regulatory Focus |
| title_sort | prevention or promotion predicting author s regulatory focus |
| url | https://nejlt.ep.liu.se/article/view/4561 |
| work_keys_str_mv | AT aswathyvelutharambath preventionorpromotionpredictingauthorsregulatoryfocus AT kaisassenberg preventionorpromotionpredictingauthorsregulatoryfocus AT romanklinger preventionorpromotionpredictingauthorsregulatoryfocus |