OPO is a bilingual (Mandarin-English) corpus containing texts of a text type/genre that can be termed Online Pet Obituaries (hence the acronym OPO). In OPO texts, bereft pet owners mourn their deceased pets in the web space. Texts were retrieved online in different fora and websites and exported in txt format, so to make them processable by most qualitative and quantitative analysis software tools. Texts were then meta-tagged in a spreadsheet for language, date of posting, cause of death of the animal, age of death, animal species, and word length (for which I have used Sketch Engine segmentation and counting; Kilgariff et al. 2014). Texts were posted between 2009 and 2022. Causes of death include euthanasia, poisoning, cancer, and beating to death; the age of deceased pets ranges from almost a year old (a cat in ID23) to more than 16 years old (a cat in ID1 and the dogs in ID13 and ID48); English texts refer to cats (n= 12) and dogs (n= 17) with one missing value (n= 1); Chinese texts refer to cats (n= 12) and dogs (n= 14), but also include three texts (n= 3) on the death of other animals such as a goldfish, a jellyfish, and a bird. The Chinese corpus has 6,200 words, ranging in word length from a minimum of 10 words to a maximum of 455 words (M = 205; sd= 241) with two outliers at 521 and 1,239 words. The English corpus has 10,717 words, ranging in word length from 19 to 680 words (M = 357; sd= 318) with three outliers at 861, 1,215, and 1,257. In terms of legal requirements, this research was conducted under Italian law and complies with copyright law nr. 633/1941 art.70-ter., 2021 amendment. Ethical aspects were also taken in due consideration. Texts were then analysed and tagged for metaphor identification by applying MIPVU (Steen et al. 2010; Wang et al. 2019) at the word level in Atlas.ti, a qualitative and quantitative software tool, largely following Kimmel’s (2012) method, who illustrates how to use that software to study metaphor in discourse, a method also applied by Silvestre-López (2020) and Nacey (2022). The creation and the study of this corpus falls within the Project of Excellence in Inclusive Humanities (2023-2027) of the Department of Foreign Languages and Literature of the University of Verona, and specifically within Work Package 1 (WP 1) on the study of human psychological and emotional wellbeing.
Online Pet Obituaries (OPO)
Michele Mannoni
2023-01-01
Abstract
OPO is a bilingual (Mandarin-English) corpus containing texts of a text type/genre that can be termed Online Pet Obituaries (hence the acronym OPO). In OPO texts, bereft pet owners mourn their deceased pets in the web space. Texts were retrieved online in different fora and websites and exported in txt format, so to make them processable by most qualitative and quantitative analysis software tools. Texts were then meta-tagged in a spreadsheet for language, date of posting, cause of death of the animal, age of death, animal species, and word length (for which I have used Sketch Engine segmentation and counting; Kilgariff et al. 2014). Texts were posted between 2009 and 2022. Causes of death include euthanasia, poisoning, cancer, and beating to death; the age of deceased pets ranges from almost a year old (a cat in ID23) to more than 16 years old (a cat in ID1 and the dogs in ID13 and ID48); English texts refer to cats (n= 12) and dogs (n= 17) with one missing value (n= 1); Chinese texts refer to cats (n= 12) and dogs (n= 14), but also include three texts (n= 3) on the death of other animals such as a goldfish, a jellyfish, and a bird. The Chinese corpus has 6,200 words, ranging in word length from a minimum of 10 words to a maximum of 455 words (M = 205; sd= 241) with two outliers at 521 and 1,239 words. The English corpus has 10,717 words, ranging in word length from 19 to 680 words (M = 357; sd= 318) with three outliers at 861, 1,215, and 1,257. In terms of legal requirements, this research was conducted under Italian law and complies with copyright law nr. 633/1941 art.70-ter., 2021 amendment. Ethical aspects were also taken in due consideration. Texts were then analysed and tagged for metaphor identification by applying MIPVU (Steen et al. 2010; Wang et al. 2019) at the word level in Atlas.ti, a qualitative and quantitative software tool, largely following Kimmel’s (2012) method, who illustrates how to use that software to study metaphor in discourse, a method also applied by Silvestre-López (2020) and Nacey (2022). The creation and the study of this corpus falls within the Project of Excellence in Inclusive Humanities (2023-2027) of the Department of Foreign Languages and Literature of the University of Verona, and specifically within Work Package 1 (WP 1) on the study of human psychological and emotional wellbeing.
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