AI-enabled Corpus Analysis: Space Science

Evidano is an AI-powered qualitative data analysis platform that ingests multilingual corpora, preserves reproducible preprocessing logs, and produces co-occurrence, thematic, and addressing-term analyses.

This post shows how to reproduce a PLOS corpus-assisted discourse study (published July 9, 2026) on Weibo and X using those features and a two-week pilot workflow that covers data ingest, preprocessing, co-occurrence mapping, coding, and cross-segment comparisons.

• The PLOS study compared Weibo (895 posts, 24, 769 tokens) and X (1, 204 posts, 25, 063 tokens) collected Apr 1–Oct 1, 2023.
• Core analyses include co-occurrence networks (Jaccard), topic clustering, and addressing-term word associations around self/audience/nation.
• Follow the 7-step reproducible workflow to run a two-week pilot and produce exportable tables, concordances, and audit logs; Evidano stores data encrypted and supports role-based access without using your data to train third-party models.

The PLOS study built two specialized corpora (Weibo and X) and applied quantitative text-mining with KH Coder plus critical discourse analysis to examine three layers: topics, addressing terms, and word associations.

The PLOS study examined (1) topics and themes using co-occurrence networks, (2) addressing terms such as self, audience, and nation, and (3) words co-occurring with self-addressing terms, finding that China’s official accounts blend state affiliation, patriotism, and interpersonal warmth while U.S. accounts emphasize professional expertise, mission execution, and interest-based audience segmentation.

• Published: July 9, 2026; data period: Apr 1–Oct 1, 2023.
• Chinese corpus: 895 posts / 24, 769 tokens. English corpus: 1, 204 posts / 25, 063 tokens.
• Analyses: co-occurrence networks (Jaccard), topic clusters, and word-association around self-addressing terms.

This 7-step workflow outlines how to reproduce a CADS like the PLOS paper in a two-week pilot using AI-enabled corpus analysis.

• 1) Collect: export or scrape public posts for target accounts (1–6 months).
• 2) Ingest: upload raw CSV/JSON to Evidano and enable language detection.
• 3) Normalize: apply lemmatization/segmentation and add custom dictionary entries (project names, mascots).
• 4) Tag: import a simple codebook (self/audience/nation) and run automated coding.
• 5) Explore: generate topic clusters, co-occurrence networks, and word associations (top 150 edges like the study).
• 6) Compare: run cross-segment frequency and time-series analyses; export tables and visualizations.
• 7) Synthesize: use Evidano’s chat-over-documents to draft an evidence brief and extract exemplars (concordance lines) for qualitative quotes.

AI-enabled corpus analysis scales corpus-assisted discourse studies across languages and platforms by automating preprocessing, mapping, coding, and cross-segment statistics while preserving qualitative depth via concordances and coded exemplars.

• Try a secure demo on Evidano to import two corpora, add a custom dictionary, generate co-occurrence networks, and produce a downloadable evidence brief in under 48 hours.
• If your work requires ethics oversight (human subjects or sensitive datasets), treat results as research-only and secure necessary approvals before analysis.

Ready to reproduce the PLOS methods on your own social corpora? Start a pilot at Try Evidano for free and get a reproducible, audit-ready workflow for AI-enabled corpus analysis.