Social Endorsement Cues (SECs) merupakan indikator seberapa banyak dukungan terhadap suatu postingan di media sosial. Semakin tinggi SECs maka informasi di media sosial akan dianggap semakin kredibel. Namun, terdapat isu metodologis yang mempengaruhi penelitian sebelumnya dan perlu diatasi, yaitu jumlah stimulus (topik berita), tampilan yang tidak realistis, dan confirmation bias. Penelitian ini menggunakan metode eksperimen secara online dengan desain 2 (keaslian berita : asli vs palsu) x 2 (tingkat SECs : tinggi rendah) within subject. Tujuannya adalah melihat pengaruh keaslian berita dan tingkat SECs terhadap persepsi kredibilitas berita di platform X dan bagaimana pengaruhnya jika mengontrol confirmation bias partisipan. Hasilnya menunjukkan bahwa berita asli dianggap lebih kredibel daripada berita palsu dan tingkat SECs harus berinteraksi dengan keaslian berita agar dapat memberikan pengaruh yang signifikan. Selain itu, confirmation bias merupakan variabel kovariat yang harus dikontrol. Penelitian ini dapat membantu mengembangkan model teoretis mengenai bagaimana individu mengevaluasi kredibilitas berita di media sosial.

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Social Endorsement Cues (SECs) are indicators of the level of support for a post on social media. The higher the SECs, the more credible the information on social media is perceived to be. However, there are methodological issues affecting previous research that need to be addressed, such as the number of stimuli (news topics), unrealistic display, and confirmation bias. This study employs an online experimental method with a 2 (news authenticity: real vs. fake) x 2 (SECs level: high vs. low) within-subjects design. The aim is to examine the influence of news authenticity and SECs level on the perceived credibility of news on platform X, and how this influence changes when controlling for participants' confirmation bias. The results show that real news is perceived as more credible than fake news, and the SECs level must interact with news authenticity to have a significant effect. Additionally, confirmation bias is a covariate that must be controlled. This study can help develop theoretical models on how individuals evaluate the credibility of news on social media.