Evaluating the Impact of Cultural Context Loss in Cross-Language Literary Adaptation

The increase in digital technologies and the emergence of cloud-based literature libraries have contributed significantly to both the occurrence and threats associated with cross-language literary adaptation. As literary works transition across linguistic and cultural borders in an internet environment, there are two types of losses experienced simultaneously: semantic-cultural degradation, where cultural context is lost during the process of translation, and security concerns involving metadata, attribution of authors, provenance data, and digital rights management (DRM). This paper proposes a dual framework approach that assesses cultural context loss (CCL) in cross-language literary adaptation by applying the concepts of internet security in terms of data integrity, authenticity, non-repudiation, and access control. Using techniques and approaches from the fields of computational linguistics, digital humanities, and cybersecurity, this study examines how translation processes implemented using internet resources create vulnerability that is similar to man-in-the-middle (MitM) attacks, where both the cultural context and digital identity can be compromised. The Cultural Integrity and Security Model (CISM) is presented here as an all-encompassing assessment model. The efficacy of this model is tested using empirical analysis through the study of three different literary translation machines. In findings, the machine-assisted literary translations at a mean CCL rate of 34.7% show strong correlation (r = 0.71, p < 0.05) with the weakness of provenance authentication procedures. Five specific areas of security weakness have been identified, and recommendations have been made for securing literary translation processes.

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