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Sarcasm in Anthony and Joe Russo’s Movie Avengers: Endgame Syamsul Bahri; Dio Manik; Fadillah Fauziah Putri; Indi Azizah Nailah
Fonologi: Jurnal Ilmuan Bahasa dan Sastra Inggris Vol. 3 No. 2 (2025): June: Fonologi: Jurnal Ilmuan Bahasa dan Sastra Inggris
Publisher : Asosiasi Periset Bahasa Sastra Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/fonologi.v3i2.1740

Abstract

Sarcasm is often used in movies to create humor, but it can also show deeper emotions like anger, disappointment, or hidden criticism. In the movie Avengers: Endgame, sarcasm is used by many characters to express their feelings and relationships in a funny but meaningful way. This research aims to analyze how sarcasm is used in the movie and to identify which types of sarcasm appear the most. The researcher used Elisabeth Camp’s theory, which divides sarcasm into four types: propositional, lexical, like prefixed, and illocutionary sarcasm. The method used is descriptive qualitative, by watching the movie, collecting sarcastic dialogues, and analyzing them based on the theory. The result shows that propositional sarcasm is the most used (43%), followed by lexical sarcasm (36%), illocutionary sarcasm (14%), and like-prefixed sarcasm (7%). From these findings, it can be concluded that sarcasm in Avengers: Endgame is not only for jokes but also helps to express the characters’ emotions, conflicts, and closeness, making the dialogue more interesting and meaningful for the audience.
Integrating Perplexity AI into Academic Research: A Study on Research Gap Analysis and Proposal Development Dio Manik; Yeni Adventry Tanjung; Rita Hartati
Fonologi: Jurnal Ilmuan Bahasa dan Sastra Inggris Vol. 3 No. 4 (2025): Fonologi: Jurnal Ilmuan Bahasa dan Sastra Inggris
Publisher : Asosiasi Periset Bahasa Sastra Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/fonologi.v3i4.2605

Abstract

This study examines how Perplexity AI is integrated into academic research, particularly its role in research gap analysis and proposal development among university students. Using a qualitative descriptive method and questionnaire data from 32 participants, the research explores students’ perceptions, benefits, and ethical considerations regarding AI- assisted research. The findings reveal that Perplexity AI improves efficiency in literature review and research gap identification, with 75% of students using it to explore research topics and 65.6% acknowledging its usefulness in recognizing trends and gaps. However, concerns remain about accuracy and source reliability, as only 56.3% fully trust AI-generated results, and many still verify information manually. The study concludes that effective use of Perplexity AI requires strong AI literacy that includes critical thinking, verification skills, and ethical awareness. These insights contribute to a broader understanding of human–AI collaboration in academic settings and highlight the need for responsible, well-guided integration of AI tools in research education.