Human communication is shaped by various factors, including linguistic structure, social context, and cognitive capacity. Among these, emotion plays a pivotal role in significantly influencing message delivery and reception. While emotional impact is prominent in social media posts, its effect in extended-format, information-rich communication, such as TED Talks, is less understood. This study focuses on six basic emotions (anger, disgust, fear, joy, sadness, and surprise) and examines their effects on TED Talk popularity using the NRC Emotion Lexicon and a BERT-based sentiment analysis model. Our findings reveal a stark contrast between social media and TED Talks: most emotions, including high-arousal emotions, have no significant effect on TED Talk viewership, and in some cases, intense emotional expressions negatively impact views. This study highlights the limited role of emotions in extended-format communication and underscores the importance of appropriate emotional expressions, shaped by context and audience expectations. By integrating transparent dictionary-based methods with contextually aware deep learning approaches, we provide a comprehensive framework for analyzing emotion-driven engagement in diverse communication settings.