Advertisements are manipulative and have the ability to shift one's perspective. Masculinity is a socially constructed concept often conveyed using an ad that presents a certain beauty standard. This research aims to show that even though they are using a non-dominant masculine model, the stereotype still exists. In fact, the media should be the one who empowers the marginalized group, instead of forcing the stereotype onto them. The research method used is a multimodal theory by Kress and Van Leeuwen. Advertisement is one of the mass media included in the multimodal discourse due to the complexity of semiotic sources in meaning-making. This complexity is a result of the messages being conveyed verbally and virtually, which created a whole unit of meaning. The research question of this study is how masculinity is represented in the MSGlow For Men's advertisement. MSGlow For Men's ad is chosen as the object because it is a unique and distinct ad for it features men from the marginalized and non-dominant masculine group. The result of the research reveals that MSGlow For Men's ad doesn't break the existing men stereotype, but marginalizes the non-dominant masculinity group. The production of the ad and the use of brand ambassadors don't aim to sell the product or break the stereotype but to support the existing stereotype and only for the sake of virality.
Digitalization has transformed individuals’ behaviour in receiving information. The changes has encourage marketer to shift their marketing strategy, from offline to online. With the existence of internet, Word of Mouth (WOM) strategy has converted to electronic Word of Mouth (eWOM)with the help of social media. eWOM itself has an advantage of raising awareness of a product, service, or a brand itself. Adopting the eWOM concept, there comes a new marketing strategy called buzz marketing, in which usually is using a third-party to maximize the viral and trending effect from eWOM. Using a case study from a beauty brand, Secondate, this paper analyzes the buzz marketing campaign that was done by Secondate on their first launching. Instead of using a buzzer, Secondate used more than 20 Indonesian influencers to create a buzz on social media and increase brand awareness of the brand Secondate. This paper alsoexplains the benefits of using influencer in eWOM instead buzzers in terms of leveraging a brand awareness. The result of this paper is that eWOM through influencer has a positive impact in increasing brand awareness, while influencers have no significant impact in customers’ purchase intention.
Kebijakan yang dibuat oleh pemerintah selama pandemi COVID-19 telah memicu kritik dari banyak pihak dalam bentuk ujaran kebencian. Penelitian ini bertujuan untuk memetakan tipologi atau tema dari ujaran kebencian di Twitter yang ditujukan kepada pemerintah Indonesia mengenai kebijakan yang dibuat selama pandemi COVID-19, sekaligus frekuensi dan pola dari ujaran kebencian yang muncul pada periode Mei – Juli 2020. Penelitian ini menggunakan metode analisis isi dengan data berupa Tweet berbahasa Indonesia di Twitter. Analisis didasarkan pada kata kunci yang didapat secara deduktif dari dataset Indonesian Abusive and Hate Speech Twitter Text. Analisis komputasional menggunakan Python menghasilkan sebanyak 1.042 cuitan bernada ujaran kebencian. Analisis manual menghasilkan 94 cuitan dengan empat tipologi hate speech yang dominan, yaitu personal attack, dehumanisasi, provokasi, dan stereotip negatif. Sasaran hate speech kepada pemerintah ditemukan ditujukan kepada tiga golongan, yakni presiden Joko Widodo, pemerintah pusat, dan pemerintah daerah secara umum. The policies established by the government during the COVID-19 pandemic have sparked criticism from the public in the form of hate speech. This research aims to map the typology and theme of hate speech towards the Indonesian government regarding the policies made during the COVID-19 pandemic as well as the frequencies and patterns of hate speech during May-July 2020. This research conducted a content analysis of tweets in Indonesian on Twitter. The analysis was based on keywords obtained deductively from the Indonesian Abusive and Hate Speech Twitter Text Dataset. The first computational analysis using Phyton obtained 1,042 tweets containing hate speech. The second manual analysis resulted in 94 tweets with four typologies of hate speech: personal attack, dehumanization, provocation, and negative stereotype. This research also found that hate speech mainly targeted three parties, President Joko Widodo, the central government, and the regional government.
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