Who Killed Sanmao and Virginia Woolf? A Comparative Study of Writers with Suicidal Attempt Based on A Quantitative Linguistic Method Shucheng Zhu 1 , Xi Wang 2 , Pengyuan Liu 1 1 School of Information Science, Beijing Language and Culture University 2 Faculty of Foreign Studies, Beijing Language and Culture University
CONTENTS Introduction Methodology 01 02 & Related Works Analysis Conclusion 03 04
PART 01 Introduction & Related Works
Introduction Sulli’s death 16 million & 8 million On 14th October 2019, Sulli - a famous It is estimated that there are 16 million Korean superstar committed suicide in her suicidal attempts each year, and own house. approximately 8 million people died of suicide*. Detecting suicide ideation and attempt Quantitative Linguistics – A new method Psychological dictionaries Internal language pattern Computer technology Different languages Social media & suicide notes *World Health Organization: Mental Health Action Plan 2013-2020. Geneva, Switzerland: World Health Organization (2013)
Related Works Literary • Literary scholars tend to consider a writer’s life as auxiliary materials in aid of textual interpretation and analysis. • Few of whom attempts to analyze literary texts for a probe into their creator’s mental condition. • Most of them apply Freudian psychoanalysis in their studies. Linguistic features and computer technologies • Find the relation between features of writing style and writers with suicidal attempts. • Psychological dictionary LIWC. • Distinguish suicidal notes and ordinary works. • Social media as microblog. • Quantitative linguistic markers.
PART 02 Methodology
Materials Virginia Woolf Sanmao
Research Questions Five quantitative linguistic markers are employed in this paper to analyze and to answer the following three research questions: • Can these markers be used in the analysis of writers of different languages? Can these markers reflect psychological activities of writers with suicidal attempt? • What can we learn from these markers? •
Markers Richness • Is a measure of a person’s ability to use vocabulary of a determined size. • Reflects not only the person’s age and education background, but also his/her mood and psychological activities. • People in a normal or joyful mood tend to have high richness than people with a bad mood. • R4 is one of the many ways of calculating vocabulary richness of a text. The bigger it is, the more richness the text is. • V is the total type of a text, N is the total token of a text, r is the rank and f(r) is the frequency in the rank-frequency distribution of a text. • Hapax Percentage is a simple ratio between the number of tokens and the number of hapax legomena in a text. Hapax legomena are the words that occur only once in a text. • NH is the number of hapax legomena in a text.
Markers Pronoun • Females prefer to use more personal pronouns and the more the pronouns they use, the more emotional the writers’ are. • People with suicidal attempts use more personal pronouns in their social media. • P is the total number of personal pronouns in a text. Sensory Words • Refer to visual, auditory, haptic, olfactory and gustatory adjectives. • Using less number and exclusivity of sensory adjectives can also be a signal of mental disease. • 𝝌 𝒋 is the number of the order i adjective in the text and 𝝒 𝒋 is the value of exclusivity of the adjective, NK is the total number of the sensory adjective list.
Markers Lambda • Is an indicator that deals with a frequency structure of a text. • Both reflects vocabulary richness and the relationship between the neighboring frequencies in a text. Zipf’s Exponent • Zipf’s exponent might be related to the language cognition and other aspects. • Children’s language Zipf’s exponent is higher than the adults’. • If the writer is in the good condition, the language Zipf’s exponent should be low. . • 𝑄 " is the frequency of the word which rank is r. C and b are exponents.
PART 03 Analysis
Correlation Analysis • Markers Richness, Sensory and Lambda have homogeneity which demonstrates that the higher the markers are, the better mood and mental condition the writers are in. • Markers Pronoun, Zipf’s Exponent has homogeneity which demonstrates that the higher the markers are, the worse mood conditions the writers are in.
Markers Visualization • For Sanmao’s works, the lowest value is about on S7, and in her last several works the values turn down. • For Woolf’s works, the lowest values belong to V1, V2 and V8, and in her last 2 works, the values go up. Sensory is an exception as in a way it predicts her worse mood and other markers show her sudden suicide because of the shock of war.
Markers Visualization • For Sanmao’s works, the high value is S7 and the values of her last 2 works go up. • For Virginia Woolf, the highest values are V1, V2, V5 and V8 and the values of her last two works go down. • The mean of Zipf’s exponent can show that Zipf’s exponent can distinguish different languages.
Sequence Clustering • V1, V2: Virginia Woolf’s earlier writings. As a novice in literature, Woolf suffered greatly from the pressure inflicted by Virginia Woolf’s works finishing the novels. So, her mood alternated between depression and euphoria. • V3, V4, V5: These three books can be seen as Woolf’s best literary creation and this period is the primetime of her career which endowed with personal matters. • V6, V7: These two books are generally considered as the best of her later career. • V8: As an anti-war outcry of Woolf, The Years is consuming for Woolf’s sensitive nerves, unstable mentality and vulnerable physicality. • V9: We can see a recovery tendency in the period between Woolf’s last two novels. However, the horrific and inexorable war accelerated Woolf’s suicidal tendency.
Sequence Clustering • S1, S2, S3, S4, S5, S6: her early works and life in Sahara. Sanmao’s works • S7: darkness of her life because of her beloved husband’s death. • S8, S9, S10: she created these works while or after she travelled in Latin America and Europe. • S11, S12: her last 2 works which indicates her suicide because her own bad mood.
PART 04 Conclusion
Conclusion We use five quantitative linguistic markers The result shows that all the markers we choose can reflect the writers’ psychological and mood activities to analyze two female writers of different both in English and Chinese. languages. With the help of these markers, we may find out the From these markers, we also find out the big event, psychological change of the writers who would such as mental disorder and the loss of spouse and never tell the public why they chose to commit war, would apparently influence one’s life. suicide to end their lives.
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