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In Yaşar Kemal‘s The Pomegranate on the Knoll, the environment of the Çukurova peasants is depicted meticulously in their daily struggle for survival; however, Kemal transcends purely realist representations whenever the characters try either to make sense of or to gain control over their hostile environment. By using magical realist strategies in his text as well, he gives a voice to the suffering of the Çukurova peasants and engages in a form of political writing different from social realism or village literature. He helps to raise public awareness for the traumatic consequences of the changing social reality in rural Turkey not only by describing it, but also by using magical realist writing strategies which let readers feel it for themselves.
Observing the Digital Self
(2021)
Facebook, Instagram, Twitter & Co. Social media have become an essential part of everyday life for many people in recent years, and as such, it is impossible to imagine a life without them. It seems self-evident to operate as an active prosumer in the net via various end devices. We create personal profiles in various social networks, exchange ideas, and connect with others. We take part in virtual events, and above all: we actively shape the web.
The photo and video platform Instagram is one of the most popular social networking sites. Since 2010, the online service has offered its users the opportunity for personal development and space for creativity. Therefore, the personal profiles serve not only participatory reasons but also facilitate acts of self-representation.
In addition to apparently visible aspects, questions about self-perception arise: How do users experience and evaluate their activities in virtual space? How do they perceive their actions between the offline and online world, and how intertwined are these spheres? Through an ethnographical approach, this work represents the attempt to look beyond the self-evident aspects of the digital self. For this purpose, two Instagram users were accompanied for more than a year.
Given a collection of diverging documents about some lost original text, any person interested in the text would try reconstructing it from the diverging documents. Whether it is eclecticism, stemmatics, or copy-text, one is expected to explicitly or indirectly select one of the documents as a starting point or as a base text, which could be emended through comparison with remaining documents, so that a text that could be designated as the original document is generated. Unfortunately the process of giving priority to one of the documents also known as witnesses is a subjective approach. In fact even Cladistics, which could be considered as a computer-based approach of implementing stemmatics, does not present or recommend users to select a certain witness as a starting point for the process of reconstructing the original document. In this study, a computational method using a rule-based Bayesian classifier is used, to assist text scholars in their attempts of reconstructing a non-existing document from some available witnesses. The method developed in this study consists of selecting a base text successively and collating it with remaining documents. Each completed collation cycle stores the selected base text and its closest witness, along with a weighted score of their similarities and differences. At the end of the collation process, a witness selected more often by majority of base texts is considered as the probable base text of the collection. Witnesses’ scores are weighted using a weighting system, based on effects of types of textual modifications on the process of reconstructing original documents. Users have the possibility to select between baseless and base text collation. If a base text is selected, the task is reduced to ranking the witnesses with respect to the base text, otherwise a base text as well as ranking of the witnesses with respect to the base text are computed and displayed on a histogram.