1、 Introduction

Big data technology is profoundly influencing social life, and its application in literary research is challenging traditional theories. Digital humanities researchers believe that big data has changed the way humanities research is conducted, and Chris Anderson suggests that mathematical tools in the era of big data may render traditional theories outdated. Victor Meyer Sch ö nberg and Kenneth Kukel support this view, believing that statistical models of big data are superior to traditional scientific models. Jeffrey Dirio believes that the threat of big data to theory is unprecedented. This article explores the significance of big data for humanities research and whether it can truly become the terminator of theory.

2、 What is big data?

Deeply explored the origin, definition, and importance of big data in modern society. Starting from the etymology of the Latin word 'data', this article elaborates on how data embodies the concept of realism and how humans understand and grasp the world through data. Archaeological discoveries indicate that ancient humans began using counting tools as early as 18000 years ago in the Uganda region. At the end of the 17th century, with the rise of the Industrial Revolution, statistics emerged in England, and data measurement became an important tool for social development. However, it was not until the widespread application of electronic computers in the 20th century that the ability of humans to collect and process data was greatly improved, and the era of big data began.

3、 What does big data mean for humanities research?

The rise of big data has sparked discussions in the humanities about the end of theory. Anderson believes that big data may mean the end of theory, while Mazoch further proposes that in the era of big data, complex algorithms and statistical tools are more valuable than theory or assumptions. Supporters believe that data-driven research will replace traditional hypothesis driven methods, while Davis pessimistically predicts that big data may replace multiple independent disciplines. Online platform merchants analyze consumer behavior through big data without having to understand advertising knowledge or consumer culture. Literary research, which is considered a non utilitarian field of free exploration, may also be influenced by big data. However, big data also brings new opportunities for humanities research, such as the macro analysis advocated by Jocks, which may provide a scientific foundation for literary research. Digital humanities technology may help humanities research break free from relativism and move towards objective and scientific goals. Ghana believes that digital humanities will drive humanities into a post theoretical era, where the production of tools and archives is more important than interpretation. Antitheorists such as Rappaport and Stedman advocate that future scholars should become data experts. Big data literature research may improve research efficiency, expand research scope, and question past hypotheses. Humanities scholars should also remain vigilant when facing the opportunities of new technologies.

4、 Critical thinking on big data methods

Deeply explored the application of big data methods in literary research and their potential critical issues. The author points out that although big data has brought technological innovation and self-renewal vitality to literary research, its deep ideological transformation may harm fundamental aspects of literary research, such as textual scrutiny and ideological criticism. Mario Aquinas emphasized the importance of maintaining a critical awareness of interdisciplinary methods in literary research. Supporters of big data methods attempt to improve the objectivity of literary research through mathematical solutions, but this technological optimism overlooks the fundamental responsibility of literary research. The objectivity of big data often avoids the role of data in shaping research results, and data is not objectively present, but needs to be regarded as data. Theoretical assumptions play a crucial role in digital humanities research, as researchers' background knowledge, interests, and research strategies can all influence the examination and measurement of data. The objective model of big data methods is considered a regression, reflecting the immaturity of philosophy. Data itself cannot speak for itself, but only for the underlying assumptions it contains. With the increase of data volume, theory plays an increasingly important role in analysis. The algorithmic culture behind big data should not be accepted uncritically, as even useful tools can create unwanted consequences. The rise of neoliberalism and anti theoretical movements has provided a suitable social soil for empirical research, and the emergence of big data or digital humanities research is a product of this background. The commonality of theories is to raise questions, distrust texts and world appearances, and hope to reveal deeper things through textual symptoms. The role of digital humanities research in the field of cultural criticism is clearly lacking, and the value of humanities research lies in achieving critical supervision of society from a special perspective. Digital technology should serve as a supplement to humanities and academia, rather than undermining the framework values and ideals of the field. Faced with the emergence of new technological conditions, literary research should cautiously accept new technologies while maintaining critical reflection.

5、 Conclusion

In the context of neoliberalism in the 21st century, the humanities are facing questions about their competitiveness in employment and contribution to economic development, and the rise of digital humanities research is seen as a response to this crisis. New technologies such as big data provide opportunities for humanities disciplines to reconnect with society, but humanities scholars need to be vigilant about how technology changes the nature of the discipline. The data-driven approach enriches research tools, but should not replace traditional methods. Anderson's "theory termination theory" has sparked debate, but big data will not end theory, but bring new opportunities. Humanities research should critically utilize new technologies, complement traditional methods, and serve research purposes.