Exploring Semantic Prosody Through Natural Language Processing (NLP) : L1 and L2 Use of the Lexical Bundle There Are So Many

This study explores the semantic prosody of the lexical bundle (LB) there are so many in native and nonnative novice English argumentative writing.While previous research on LBs has largely focused on their structural and functional patterns, this study shifts attention to their evaluative meanings in context.Using NLP-based sentiment analysis, it examines how this bundle conveys evaluative stance across two comparable corpora: one consisting of argumentative essays written by native English-speaking students and the other by Korean EFL learners.Both groups were incoming college freshmen who responded to the same prompts under identical time constraints.The results exhibited a clear difference in semantic prosody: native writers tended to use the bundle in neutral or positive contexts, often to hedge or provide examples, whereas non-native writers used it more frequently in negative contexts, which could lead to semantic incongruity or pragmatic misalignment.These findings move beyond existing accounts of LBs by highlighting the role of evaluative meaning.They suggest that L2 learners may benefit from explicit instruction on how stance is expressed in frequently occurring word sequences-an area particularly challenging for novice academic writers.This study highlights the value of sentiment-aware writing pedagogy, as informed by corpus-based insights into learner language.