Intensity of Emotions and Narrative Structure Tibor Pólya Institute for Psychology Hungarian Academy of Sciences.

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Intensity of Emotions and Narrative Structure Tibor Pólya Institute for Psychology Hungarian Academy of Sciences

SDH 2010, October, Vienna Different Methods for Automated Analysis of Emotions Emotion labels –Pennebaker: LIWC (915 emotion labels in 5 categories) Emotional connotation of words –Whissel: DAL (8742 words scored for evaluation, activation and imagery) Identifying theory based emotion relevant categories in narratives –Stein: Narcoder (14 categories, e.g. precipitating event, emotion and mood states, beliefs, goal, action, outcome…) Narrative structure

SDH 2010, October, Vienna Structural Analogy Emotional state has components –Appraisal processes –Subjective experience –Physiological changes –Expressions –Action tendency Evaluation Temporal unfolding Reflectivity Emotional States and Narratives have analog structure

SDH 2010, October, Vienna Structural Analogy 1. Evaluation Emotional states are caused by appraised events Narrative: Events + Evaluations

SDH 2010, October, Vienna Narrative Evaluation Default narrative structure: Successive chain of events Elaborated narrative structure: Events + Evaluations

SDH 2010, October, Vienna Structural Analogy 2. Temporal unfolding Emotional states are time bound and dynamic Narrative: Temporal contour

SDH 2010, October, Vienna Temporal Unfolding Default narrative structure: Punctual events Elabortaed narrative structure: Rich temporal organization Temporally extended event I was sitting … Temporally salient event I was there already … Explicit sequencing of events Later …

SDH 2010, October, Vienna Structural Analogy 3. Reflectivity Emotional states can be reflected or non-reflected Narrative: Spatio-temporal perspective

SDH 2010, October, Vienna Spatio-temporal Perspective Retrospetive form I was there … Experiencing form I see you … Meta-narrative form I remember … Deictic center

SDH 2010, October, Vienna Linguistic Markers: Narrative Evaluation (Labov, 1982) Types of Evaluation –External Direct evaluation Past evaluative remark –Embedded –Evaluative action –Suspension of the action Elements of Evaluation –Intensifiers Quantifiers Repetition Ritual utterance –Comparators Negated event Modal expression Future events –Correlatives Progressive –Explicatives Qualification Causal explanation

SDH 2010, October, Vienna Linguistic Markers: Narrative Evaluation Types of Evaluation –External Direct evaluation Past evaluative remark –Embedded –Evaluative action –Suspension of the action Elements of Evaluation –Intensifiers Quantifiers Repetition Ritual utterance –Comparators Negated event Modal expression Future events –Correlatives Progressive –Explicatives Qualification Causal explanation

SDH 2010, October, Vienna Linguistic Markers: Temporal Unfolding Verbal aspect –Continuous –Perfect (verb prefix) Temporal adverbs –Temporally salient event (e.g. I was sitting already in the car …) –Explicit sequencing of events (e.g. later)

SDH 2010, October, Vienna Linguistic Markers: Spatio-temporal perspectives Verb time (morphological analysis) –Present (and Future) –Past Temporal and Spatial Deictic terms –Proximal (e.g. now, here) –Distal (e.g. then, there) Characteristic words –Retrospective: some temporal adverb without verb (e.g then) –Experiencing: interjections (e.g. hoops) –Meta-narrative: some mental verb term in present tense with I as subject (e.g. I remember…)

SDH 2010, October, Vienna NooJ Silberztein (2008) Linguistic Preprocessing –Hungarian linguistic resources for NooJ (Váradi & Gábor, 2004) –Hungarian tool chain tokenization (built-in NooJ module) sentence splitting lemmatization, morphology (Vajda et al., 2006): inflectional dictionary for lemmata + lookup: frequent word forms from the HNC to achieve better coverage, the output of the NooJ-internal morphology was completed with the Humor morphological analyzer (Prószéky, 1995) Rule-based syntactic parser is included in the Hungarian NooJ module (Váradi, 2003; Gábor, 2007) User-friendly interface: easy to handle, develop, share and re-use grammars

SDH 2010, October, Vienna Qualifier Grammar

SDH 2010, October, Vienna Reliability (16 stories, 1312 narrative clauses, coded by 3 judges) Recall % Precision % Narrative Evaluation Temporal Unfolding Spatio-temporal Perspective

SDH 2010, October, Vienna Validation: Empirical Study Hypothesis: If a story has an elaborated narrative structure the intensity of an emotional state during narration is higher than the story has a default narrative structure Default narrative structure –Core narrative clauses –Chain of punctual events –Retrospective perspective form Elaborated narrative structure –Evaluative narrative clauses –Rich temporal structure –Experiencing and meta-narrative perspective forms

SDH 2010, October, Vienna Baseline Physiological Measures, 2 mins HR, RESP, SC Affective Grid: Baseline Cue Word: Pride Excitement Relief Fear Sadness Embarrassment Narration and Continuous Physiological Measures: HR, RESP, SC Affective Grid: Past Affective Grid: Present

Results: Physiological measures 107 stories from 18 subjects Relative frequenciesHeart Rate Mean Heart Rate Amp. Respiration Mean Respiration Amplitude Skin Conduc. Narrative evaluation-.16* Past direct evaluation.21**.14*.13* Quantifier-.13*-.18** Negated event Modal expression.17** Qualifier-.28***-.13* ST Perspective Retrospective-.14*.13* Experiencing-.23** Meta-narrative-.29***.21** Temporal unfolding Continuous verb aspect.13*-.19* Temporal salience-.17* Sequencing.18* *** p < 0.01; ** p < 0.05, * p < 0.10

Results: Physiological measures 18 stories, Cue word: Relief Relative frequencies of structural features Heart Rate Mean Heart Rate Amp. Respiration Mean Respiration Amplitude Skin Conduc. Narrative evaluation Past direct evaluation Quantifier-.41** Negated event-.34*.40** Modal expression.34*.50**-.42** Qualifier.45**-.37* ST Perspective Retrospective-.51**-.54** Experiencing34* Meta-narrative.43**.53** Temporal unfolding Continuous verb aspect-.38* Temporal salience.36*.42** Sequencing ** p < 0.05, * p < 0.10

SDH 2010, October, Vienna Conclusions We are able to automatically analyse narrative structure It is promising to use deep linguistic description to this end Narratives are proper tools for reliving and sharing emotion experiences We can study emotion through the structure of narratives

SDH 2010, October, Vienna Thank you for your attention! Bea Ehmann Kata Gábor Tilmann Habermas Piroska Kabai Norbert Kollárszky Ildikó Kovács János László Anthony Marcel Erika Szatmári Hungarian Scientific Research Fund Bolyai Research Scheme

SDH 2010, October, Vienna

Analysis of Narrative Structure versus Content Content Category: based on meaning Representation Face validity Narrative Structure Feature: linguistic markers with same function Construction Deeper level of validity Story world TextNarration

Results: Self-report measures Arousal Past Arousal Present Abs. Valence Past Abs. Valence Present Narrative evaluation.21**-.19**-.13* Past direct evaluation.13* Quantifier Negated event.13* Modal expression-.14*.16* Qualifier-.14*.15* ST perspective Retrospective.20** Experiencing-.13*-.14* Meta-narrative-.21**-.16* Temporal unfolding Continuous verb aspect Temporal salience Sequencing

SDH 2010, October, Vienna Structure of the Presentation Methods for automated analysis of emotions in psychology Reasons for studying narrative structure Automated analysis of narrative structure Empirical study for validation

SDH 2010, October, Vienna Role of Narratives in Emotion Research Narratives describe emotional responses –Stein, Trabasso, Folkman, Richards (1997) Narratives genarate emotions in readers –Oatley (1999) Narratives provide definition for emotions –Hogan (2004) Narratives are tools for reliving and sharing emotional experiences

SDH 2010, October, Vienna Conclusions We can study emotion through the structure of narratives Narratives are proper tools for reliving and sharing emotion experiences Narrative structure opens a window on construction processes, on-line A new and a non-invasive way for studying rather elusive emotion states It is promising to use deep linguistic description to analyse narrative structure

SDH 2010, October, Vienna

Automatically Analysed Structural Features Narrative Evaluation –(Core narrative clauses) –Quantifiers –Qualifications –Negated events Temporal Contour –Perfect verb aspect –Continuous verb aspect –Specific temporal adverbs Spatio-temporal Perspective Forms –Retrospective –Experiencing –Metanarrative

SDH 2010, October, Vienna Further work Analysis of –A whole Corpus –More linguistic markers –Patterns of narrative structure, not simply relative frequencies English corpus

SDH 2010, October, Vienna Narrative Evaluation and Physiological Measures Strong, but reverse correlations r Proud =0.70 p<0.01 r Fear =-0.66 p<0.01

SDH 2010, October, Vienna Temporal Contour and Physiological Measures Strong, but reverse correlations r Excitement =0.70 p<0.01 r Fear =-0.68 p<0.01

SDH 2010, October, Vienna Perspective and Physiological Measures r=-0.70 p<0.01 r=-0.60 p<0.01

SDH 2010, October, Vienna Perspective and Physiological Measures r=0.63 p<0.01 r=-0.64 p<0.01

SDH 2010, October, Vienna Narrative Structure and Affective Grid Strong negative correlations r Pride =-0.62p<0.01 r Fear =-0.65p<0.01 r Excitement =-0.67p<0.01