Purpose-It is necessary to develop different crisis management strategies in order to understand their own images on consumers and to change the negative attitudes and perceptions to the positive ones. In this study, social media users' attitudes towards two different brands during the crisis were examined. The main purpose of this study is to give suggestions regarding the communication strategies that brands will develop through social media. Methodology-Based on the text mining method, sentiment analysis was performed with Google Natural Language Processing on the data obtained from the Twitter which is a social media platform. Findings-According to the results of the sentiment analysis conducted for two different brands, it is seen that social media users express a positive attitude to one of the firms, while they express a negative attitude to the other one. Conclusion-In this study, the reasons of different attitudes of social media users were discussed. The reasons for this difference are thought to be because of the different sectors the companies belong to, different product category and their pricing strategy.
Yüksek inovasyon içeren ürünlerde tüketicilerin algıladıkları risk yüksektir. Özellikle yüksek teknoloji ürünlerinde satın alma risk seviyesi bireyin ürünü tercih etme risk seviyesini aşabilir. Bu nedenle yüksek teknoloji ürünleri satan markaların tüketicilerin risk algısını azaltma stratejileri uygulaması gerekmektedir. Bu çalışmada yüksek teknoloji ürünlerine sahip olan markaların belirli ürünleri için gerçekleştirdikleri radikal ve artımsal inovatif ürün özelliklerine karşı tüketicilerin tutumları incelenmiştir. Tüketici tutumlarının incelenmesi için sosyal medya kullanıcılarının markaların lansman döneminde üç ay boyunca artımsal ve radikal ürün özellikleri ile ilgili Twitter üzerinden yaptıkları paylaşımlar çekilerek veri seti oluşturulmuştur. Bu araştırmada, sosyal medya verileri üzerinde duygu analizi yapılarak tüketicilerin tutumları elde edilmiştir. Araştırma sonuçlarına göre kullanıcıların markaların radikal veya artımsal inovatif özellik içeren ürünleri hakkında yaptıkları paylaşımlarda, rakip firmaların ürünleri ile bu markaların ürünlerini kıyasladıkları görülmektedir. İki farklı marka takipçilerinin paylaşımları karşılaştırıldığında artımsal inovasyon destekleyicilerinin iki farklı markaya karşı farklı tutumlar sergiledikleri ve bu tutumların genel olarak pozitif olduğu bulgusuna ulaşılmıştır.
The objective of this study is to investigate how the brands response to the customers' complaints which are posted to brands' social media help desk accounts and how the complaint managements affect the customers' sentiments by examining the complaints and requests about the purchased products. In this regard, the data obtained from the social media network are evaluated by sentiment analysis. It is found that the sentiment value of the customers' posts, the complaint management of social media help desk and the length of the engagement (the number of question and answer) affect the customers' attitudes and posts' sentiment value. The analysis results obviously showed that the brands discussed in this study immediately reply the requests and complaints posted to their social media help desk accounts. Huge brands act considering the service recovery paradox theory and make customers happy having problems with and complain about their products. Accordingly, these customers become loyal customers.
Purpose-Many forms of brands' posts such as cointaining web links, images, photos and videos can be used for marketing research. The aim of this study is to present an approach to gather and analyze social media data and shows how marketers can derive useful outcomes from these data. Methodology-The impacts of media types (link, text, video, photo), length, time (day-of-week and time-of-day) of brands' posts on customers' engagement are investigated. For this purpose, we propose a conceptual framework and mathematical model. Findings-According to the conceptual framework and mathematical model given in this research, it is recommended to determine the effects of the content of the brands' posts on social media users. Conclusion-Brands may determine the most effective content of the social media posts by applying the proposed mathematical model in this study.
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