gender discrimination in literature; The probability of male characters in books is four times that of female characters

Today is the time of awareness and study and exploration of everything that has divided human beings in terms of gender, belief, class, Race and... have kept them apart and in injustice. Good or bad (an analyst somewhere wrote that we fundamentally have a problem with globalization and history proves this) we are no longer facing a world where its inhabitants want one gender, class, race or belief to have priority over another or others. Therefore, if we want to move forward with the world, which is better, or is this the desire of a part of the human society, maybe the time has come that with the help of science and research and human findings in this way, i.e. moving towards an equal world, by shedding light on inequalities. Let's overcome these borders and build a freer world for ourselves and future generations. In this regard, a recent study on gender discrimination in literature has been conducted, which shows that the probability that the characters in the book are male is four times the probability that they are female.

BingMag.com gender discrimination in literature; The probability of male characters in books is four times that of female characters

Today is the time of awareness and study and exploration of everything that has divided human beings in terms of gender, belief, class, Race and... have kept them apart and in injustice. Good or bad (an analyst somewhere wrote that we fundamentally have a problem with globalization and history proves this) we are no longer facing a world where its inhabitants want one gender, class, race or belief to have priority over another or others. Therefore, if we want to move forward with the world, which is better, or is this the desire of a part of the human society, maybe the time has come that with the help of science and research and human findings in this way, i.e. moving towards an equal world, by shedding light on inequalities. Let's overcome these borders and build a freer world for ourselves and future generations. In this regard, a recent study on gender discrimination in literature has been conducted, which shows that the probability that the characters in the book are male is four times the probability that they are female.

Researchers at the USC Faculty of Engineering Using artificial intelligence, USC Viterbi analyzed more than three thousand English books in the form of short stories, poems and novels, from science fiction and adventure to mystery and romance. The research team found that male characters were four times more likely to appear in books than female characters, although this decreased in works written by women. There were also more negative terms associated with female characters, such as "weak" and "stupid" versus "strong" and "power" for men. Author Mayank Kejriwal says: "Gender discrimination is real, and the fact that we see women four times less often in literature affects the subconscious of people who are influenced by this culture."

This research, by USC's Institute of Information Sciences was conducted, inspired by other research that had been conducted in the field of indirect sex discrimination, which had only yielded qualitative results. The team, of which Kejriwal is a member, wanted to use artificial intelligence techniques to calculate the presence of men and women in literature and the wider media. To produce these findings, Kejriwal and his colleague Akaresh Nagaraj accessed the data through the Project Gutenberg collection to build a database of texts from which to work.

The methods they used, Nagaraj says, And also the findings revealed a wider understanding of discrimination and its meaning in society. He added: "Books are a window to the past, and the writings of these authors give us a view of how people see the world, and how the world has changed." They can find out how many women have been in literature, including a method called nominal entity recognition (NER), which is used to extract gender-specific characters. The issue was to see how many female pronouns were used in a book compared to male pronouns. Another method is to see how many of the main characters in the book are women."

This method allowed researchers to determine whether the male characters, in about three thousand stories published from 1880 to 2000, Are the central characters of the story or not? The findings of the research also showed that in the works written by female authors, the differences between male and female characters are reduced. They showed themselves to be much more accurate than the male authors.

There were limitations in the methods used by the team; For example, if it was not clear whether the author was male or female, this issue would be ignored.

Kejriwal says: "When we published the database article, the audience criticized that we ignored non-binary genders. But we somehow agree with them. We think these issues were covered up, and we couldn't find many transgender or non-binary people.

Kejriwal admitted that a proper AI tool is yet to recognize plural words like 'they'. which might have been applied to a non-binary person.

They hope that the methods they have devised can be a cornerstone for future studies that cover these issues more effectively. This research also provides a map for future work in calculating those qualitative findings that were discovered during the methodology of this research. Regardless of natural biases in human-designed studies, the AI was able to identify traits that were associated with gender-specific characters.

Nagaraj says: "Even taking into account the percentage of error, the words used about women Gone were traits such as weak, charming, beautiful and sometimes stupid. For the male characters, the words that described them included leadership, power, force, and politics.

This team Research says that although they didn't quantify this part of their research, the difference in character descriptions of different genders should be considered in the future. They added that it would be better to conduct more comprehensive qualitative studies on the relationship between vocabulary and gender. Kejriwal says: "Our studies show that the real world is complex, but all the different groups in our society who participate in cultural exchanges , have their own strengths. When we do this, we will have a more realistic view of society." Kejriwal hopes that this research will help emphasize the importance of interdisciplinary research; It means using artificial intelligence to clarify social problems and inequalities that are seen. The findings of this research have been published in the newspaper Data in Brief.

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