Publication: Sosyal medyada kadına yönelik tutum : Twitter içerik analizi
Abstract
Bu araştırma, sosyal medyada kadına yönelik tutumu incelemeyi amaçlamaktadır. Araştırmada, kullanıcıların kendilerini tanıtma, gösterme, açıklama ve kanıtlama arzularının kolay bir şekilde karşılık bulduğu ve iletişim kurmak amacıyla en sık tercih edilen sosyal medya platformu olan Twitter’ı örneklem olarak seçilmiştir. Twitter ağını kullanan kullanıcıların paylaştıkları tweetler arasından araştırma amacı doğrultusundaki kelimeleri içeren güncel tweetler aracılığıyla sosyal medyada kadın ile ilgili düşünce ve duygular kavramlar üzerinden ele alınarak, sosyal medyada kadınların nasıl bir tutumla tanımlandıklarını betimlenmeye çalışılmıştır. Bunun için hedefe uygun gelen içerik analizi yöntemi olarak tematik analiz deseni kullanılmış ve görüntü, ses, metin gibi çeşitli verilerin analizinde kullanılan, araştırmacılara hız ve kolaylık sağlayan MAXQDA Plus 2022 analiz programıyla analiz yapılmıştır. İlgili başlıklarla Ocak 2021- Mayıs 2022 tarihleri arasında yapılan taramalar sonucu 7400 tweet incelenmiş, bu tweetler içerisinde herhangi bir duygu, düşünce bildirmeyen, tweet sahibi kişilerin tutumları hakkında bilgi vermeyen, kadın algısından bahsetmeyen tweetler elenmiş. Betimlenebilecek 352 tweet analize alınmış ve tematik analize tabi tutulmuştur. Analiz sonucunda bu 352 tweete kod atanmasıyla kod kitapçığı oluşturulmuştur. Kod kitapçığı içerisinde yer alan kodların benzer kategorilerde ele alınabileceği fark edilmiştir. Bu doğrultuda kadına yönelik tutum teması altında; iyimser, güç odaklı, empatik, cinsiyete dayalı söylem, çaresiz, toplumsal cinsiyet yüklemeleri üzerinden eleştiri ve yargılayıcı olmak üzere 7 kategori belirlenmiştir. Bu kategoriler altında alt kategoriler ise şu şekildedir: iyimser kategorisinde güvenen, ilgili, umutlu; güç odaklı tutum kategorisinde; güçlü, yüce, kendine yeten; empatik tutum kategorisinde; kadını anlayan, tarafsız; cinsiyetçi/ ayrımcı tutum kategorisinde kadını suçlayan, erkeği suçlayan, kadını kısıtlayan, kadını yetersiz gören; kalıplaştıran tutum kategorisinde; ev kadını rolü, davranış beklentileri, erkeğe hizmet etme rolü, cinsel/ fiziksel görünüm beklentisi; kaba tutum kategorisinde; agresif dille yaklaşan, ahlaki yönden yargılayan, eleştiren olmak üzere 20 kod bölümüne yer verilmiştir. Elde edilen kod ve kategoriler sosyal medyadaki kadına yönelik tutum çeşitliliğini göstermektedir. Kadına yapılan yüklemelerin olumlu-olumsuz tutum kategorileriyle sınırlandırılamayacak kadar geniş şemsiye altında olduğu görülmüştür. Kadına yönelik tutumların ağırlık yükünün olumsuz tutumlarda olduğu tespit edilmiştir. Olumlu kabul edilebilecek tutumlar kadını aşırı yüce görerek gerçekten uzak bir yük altında değerlendirmektedir.
This study aims to examine the attitude towards women in social media.The sample of the research is specified as Twitter, which is the most preferred social media platform for communication and the easiest way for users to promote, show, explain and prove themselves. By discussing thoughts and feelings about women in social media through concepts, it has been tried to define how women are described in social media and with this aim, among the tweets posted by the users of Twitter network current tweets containing the words that fit for research purpose have been analyzed. Thematic analysis design, which is suitable for the target, has been used as the content analysis method. Descriptive analysis has been carried out with the MAXQDA Plus 2022 analysis program, which is used in the analysis of various data such as image, sound, text and provides speed and convenience to researchers. As a result of the scans made with the relevant titles between January 2021 – May 2022, 7400 tweets were examined and tweets that do not express any feelings, thoughts and do not provide information about the attitudes of the people were eliminated. 352 tweets that could be identified has been analyzed and subjected to thematic analysis. As a result of the analysis, a code booklet has been created by assigning codes to these 352 tweets. It has been noticed that the codes in the code booklet can be handled in similar categories. Accordingly, under the theme of attitude towards women 7 categories have been generated which are optimistic, power-oriented, empathetic, gender-based discourse, helpless, criticizing and judgmental over gender attributes. Then, 20 code sections are included as their sub-categories. The code sections under the category of optimistic are trusting, interested, hopeful; the code sections under the category of power-oriented are strong, sublime, self-sufficient; the code sections under the category of empathetic are understanding women and neutral; the code sections under the category of gender-based discourse are accusing women, accusing men, restraining women, seeing women as deficient; the code sections under the category of stereotyping are expecting housewife roles, serving men, sexual/ physical appearance expectation; the code sections under the category of impolite approach are using aggressive language, moral judgment and criticizing. The codes and categories obtained show the diversity of social media's attitudes towards women. It has been observed that the attributions made to women are under such a broad umbrella that they cannot be limited to positive-negative attitude categories. It has been detected that the weight of attitudes towards women is in negative attitudes. Attitudes that can be said to be positive see women as excessively high and evaluate them under a burden that is far from reality.
This study aims to examine the attitude towards women in social media.The sample of the research is specified as Twitter, which is the most preferred social media platform for communication and the easiest way for users to promote, show, explain and prove themselves. By discussing thoughts and feelings about women in social media through concepts, it has been tried to define how women are described in social media and with this aim, among the tweets posted by the users of Twitter network current tweets containing the words that fit for research purpose have been analyzed. Thematic analysis design, which is suitable for the target, has been used as the content analysis method. Descriptive analysis has been carried out with the MAXQDA Plus 2022 analysis program, which is used in the analysis of various data such as image, sound, text and provides speed and convenience to researchers. As a result of the scans made with the relevant titles between January 2021 – May 2022, 7400 tweets were examined and tweets that do not express any feelings, thoughts and do not provide information about the attitudes of the people were eliminated. 352 tweets that could be identified has been analyzed and subjected to thematic analysis. As a result of the analysis, a code booklet has been created by assigning codes to these 352 tweets. It has been noticed that the codes in the code booklet can be handled in similar categories. Accordingly, under the theme of attitude towards women 7 categories have been generated which are optimistic, power-oriented, empathetic, gender-based discourse, helpless, criticizing and judgmental over gender attributes. Then, 20 code sections are included as their sub-categories. The code sections under the category of optimistic are trusting, interested, hopeful; the code sections under the category of power-oriented are strong, sublime, self-sufficient; the code sections under the category of empathetic are understanding women and neutral; the code sections under the category of gender-based discourse are accusing women, accusing men, restraining women, seeing women as deficient; the code sections under the category of stereotyping are expecting housewife roles, serving men, sexual/ physical appearance expectation; the code sections under the category of impolite approach are using aggressive language, moral judgment and criticizing. The codes and categories obtained show the diversity of social media's attitudes towards women. It has been observed that the attributions made to women are under such a broad umbrella that they cannot be limited to positive-negative attitude categories. It has been detected that the weight of attitudes towards women is in negative attitudes. Attitudes that can be said to be positive see women as excessively high and evaluate them under a burden that is far from reality.