Google Autocomplete Search Algorithms and the Arabs' Perspectives on Gender: A Case Study of Google Egypt

Linda S. Al-Abbas, Ahmad S. Haider, Riyad F. Hussein

Abstract


Search engines have become an essential part of everyone's life, with Google being the most popular. Google Search provides the autocomplete feature for faster and easier search results, offering 10 top suggestions at a time, and these may influence how users view different social groups.  Different scholars have explored online discourse to reveal stereotypes about certain groups. However, little or no attention has been paid to technological affordances to reveal broader gender biases and stereotypes in the Arab World. This study examines how Google autocomplete searches can reflect the Arabs' perspectives on gender. Google Egypt is selected since it is top-rated in the number of internet users. Google is queried by entering a combination of Arabic question words followed by the Arabic equivalents for men and women. One hundred and ninety questions were generated and categorized according to the qualities they referenced. The most common assumptions about men indicate that they are cheaters, liars, self-dominant, emotionally strong, and smarter than women. They are also stereotyped as being more likely to admire young women, prefer sons over daughters, and desire polygamy. Women, on the other hand, are stereotyped as plotting, materialistic, emotional, and sensitive. The study concludes that since such generalizations may entail exaggerations and are not evidently right all the time, one must be careful about adopting such stereotypes and making them part of each gender's views of the other. Bearing in mind the perpetuating function that technology may have of existing stereotypes and social norms, users and developers of Google alike must pay more attention to gender biases that algorithms may establish and disseminate.

 


Keywords


Arabic; Google's Autocomplete; Anonymity; Stereotypes; Gender; Online Discourse

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DOI: http://dx.doi.org/10.17576/gema-2020-2004-06

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