arXiv:2605.29367v1 Announce Type: new 
Abstract: When workers lose jobs to AI-driven restructuring, two very different conversations happen on X (formerly Twitter) at the same time. Tech executives and AI researchers talk about productivity, transformation, and opportunity. Laid-off workers and labour critics talk about job loss, uncertainty, and fear. This paper asks a simple question: which conversation gets more reach? We report three studies using two collection methods and 763 tweets from 20 named public accounts. Study 1 used keyword-based collection (n=392) and found no significant difference between corpora (p=0.891), revealing that keyword search is too noisy for this task. Study 2 used account-based collection (n=96) and found a 3.12x mean amplification advantage for capital discourse over labour discourse (p=0.000003, Cohen's d=0.555). Study 3 combined both methods (n=763) and confirmed the finding at 4.18x mean and 10.77x median amplification ratio (p<0.000001). Critically, after normalising for follower count, the asymmetry persists at 2.69x (p=0.000009, Cohen's d=0.491), demonstrating that the effect is not simply a consequence of capital accounts having larger audiences. The finding is robust across all tested amplification metric weightings. We introduce the Amplification Ratio and Amplification Normalisation Index as simple metrics for measuring platform-level discourse inequality. A cross-platform replication on Reddit (n=647 posts) did not replicate the finding, suggesting the asymmetry may be specific to X's account-based amplification architecture. We discuss the methodological implications for cross-platform discourse analysis.

أظهر تحليل حسابي حديث وجود تباين كبير في الخطاب حول تسريحات العمل المتعلقة بالذكاء الاصطناعي على منصة X (المعروفة سابقًا بتويتر)، حيث يبرز تباين واضح بين روايات التنفيذيين في مجال التكنولوجيا والباحثين في الذكاء الاصطناعي، الذين يركزون على الإنتاجية والفرص، وبين العمال المفصولين ونقاد العمل، الذين يعبرون عن مخاوف بشأن فقدان الوظائف وعدم اليقين. وجدت الدراسة أن خطاب رأس المال حصل على ميزة تضخيم متوسطة تبلغ 4.18 مرة مقارنة بخطاب العمل.

Un reciente análisis computacional ha revelado una disparidad significativa en el discurso sobre los despidos relacionados con la IA en X (anteriormente Twitter), destacando un marcado contraste entre las narrativas de los ejecutivos tecnológicos e investigadores de IA, que se centran en la productividad y las oportunidades, y las de los trabajadores despedidos y críticos laborales, que expresan preocupaciones sobre la pérdida de empleo y la incertidumbre. El estudio encontró que el discurso capitalista recibió una ventaja de amplificación media de 4.18 veces sobre el discurso laboral.

Une récente analyse computationnelle a révélé une disparité significative dans le discours entourant les licenciements liés à l'IA sur X (anciennement Twitter), mettant en lumière un contraste frappant entre les récits des dirigeants technologiques et des chercheurs en IA, qui se concentrent sur la productivité et les opportunités, et ceux des travailleurs licenciés et des critiques du travail, qui expriment des préoccupations concernant la perte d'emploi et l'incertitude. L'étude a révélé que le discours capitaliste a reçu un avantage d'amplification moyen de 4,18 fois par rapport au discours…

A recent computational analysis has revealed a significant disparity in the discourse surrounding AI layoffs on X (formerly Twitter), highlighting a stark contrast between the narratives of tech executives and AI researchers, who focus on productivity and opportunity, and those of laid-off workers and labor critics, who express concerns about job loss and uncertainty. The study found that capital discourse received a 4.18x mean amplification advantage over labor discourse.