The objectives of this research were to observe the language attitude and factors determining language choice of English Department students of Bina Nusantara University. The observation carried out by exploring the motivation, language choice, and language practice of the English Department students. The data were collected through a questionnaire, which was designed to capture the students’ motivation in studying English, language choice, and practice. The result of this research shows that the English department students hold the positive attitude toward English, which are shown through the statement of the majority of the students who argue that English is an international language and offers more career opportunities. The two main factors determining the use of English are the role of the lectures and the English language exposure in the academic environment. This result is expected to provide a context to design an effective English learning process to encourage students in practicing the language.

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This research was conducted by using textual, qualitative approach while looking closer at the significant of the information that was produced in the form of photography. The aim of this research was to take a stance of the importance of photography as archives and cultural memory in its ability in promoting truths. Photography was observed as three forms; they were singular, plural, and archival. Singular forms suggested the selective association between the photographers and the photographs were taken. Plural formed resonance ideas and overall aspects in what sets of photography could bring. Archival forms offered memories as references. The result of this research shows that photography, despite its ability or inability in promoting truths, is a great pool of resources of gaining information and tracing history. Further to this research, looking closer to current social media applications that put photography forward can be one option to explore within this topic.

Ever since the emergence of digital technology at the end of the twentieth century, human communication has been mediated by digital alternatives, including social media. In the light of digital technology-based communication, this paper poses the question: what has transformed in human communication at the advent of digital age? By using qualitative method, this article discusses technology-infused human social urgers as reflected in digital storytelling, virtual communities, and other social media practices. The findings are 1) mediatization is the result of digital technology, especially that of the Internet, however 2) gathering and exploring digital data continue to be a challenging issue. The goal of this paper is to argue social media mediated communication is not just a form of mediation by, more critically, a form of mediatization. The paper aims at offering a critical review that summarizes research and discussion across the past decade and opens up opportunities in further exploring digital humanities approach on research in social media topics.

Sarcasm is the use of words commonly used to ridicule someone or for humorous purposes. Several studies on sarcasm detection have utilized different learning algorithms. However, most of these learning models have always focused on the contents of expression only, thus leaving the contextual information in isolation. As a result, they failed to capture the contextual information in the sarcastic expression. Moreover, some datasets used in several studies have an unbalanced dataset, thus impacting the model result. In this paper, we propose a contextual model for sarcasm identification in Twitter using various pre-trained models and augmenting the dataset by applying Global Vector representation (GloVe) for the construction of word embedding and context learning to generate more sarcastic data, and also perform additional experiments by using the data duplication method. Data augmentation and duplication impact is tested in various datasets and augmentation sizes. In particular, we achieved the best performance after using the data augmentation method to increase 20% of the data labeled as sarcastic and improve the performance by 2.1% with an F1 Score of 40.44% compared to 38.34% before using data augmentation in the iSarcasm dataset.