Qualitative analysis of children's social media

Evidano is an AI-powered qualitative data analysis platform that ingests PDFs, ODS tables, transcripts, and CSVs to produce thematic, cross-segment, and auditable insights for policy and research teams.

The DfSIT report published on 15 July 2026 combines two nationally representative surveys (parents and children) with open consultation annexes, and those annex ODS files are ideal for thematic coding and cross-segment comparison.

• Ingest the report PDF and Annex A–D ODS files to preserve respondent metadata and verbatim consultation responses for thematic and differential analysis.
• Combine representative polling (parents vs children) with thematic counts and exemplar quotes to produce decision-ready briefs that show both scale and texture.
• Use Evidano's automated theme extraction, co-occurrence visualizations, and clickable evidence to deliver auditable memos and stakeholder-ready visuals in days.

The report, published 15 July 2026, compiles quantitative polling and qualitative consultation about children's social media use, perceived harms and benefits, views on an under-16 ban, and attitudes toward AI chatbots and age assurance.

• Authors / publisher: Department for Science, Innovation and Technology; surveys run by Savanta.
• Primary inputs: 2 nationally representative surveys (parents; children and young people) plus public consultation annexes (multiple ODS tables).
• Why it matters: clear stakeholder split, parents and children often prioritise different harms, making cross-segment analysis essential for policy decisions.

The study used representative polling for parents and for children and young people, supplemented by open consultation responses and targeted qualitative engagement, with annex tables available in ODS format.

• Scope: attitudes to platform-level bans (under-16), feature and time limits, AI chatbot risks and benefits, and age assurance views.
• Useful artifacts: raw consultation responses and annexed tables (Annex A–D), ideal for thematic coding, sentiment checks, and cross-segment comparisons.

This 7-step workflow takes about a week to reproduce and extend the DfSIT analysis using AI-assisted tools.

• 1) Collect assets: download the PDF and Annex A–D ODS files from the report (see Children's wellbeing online (final report)).
• 2) Ingest: upload PDFs and ODS to Evidano; map respondent metadata such as age band and parent or child.
• 3) Auto-code: run initial theme extraction to surface the top 20 themes across the corpus.
• 4) Refine codebook: import or edit codes and apply supervised coding to ensure consistency.
• 5) Cross-segment analysis: run frequency and differential sentiment reports comparing parents versus children and age bands.
• 6) Visualize & extract quotes: generate a co-occurrence network and prepare a one-page brief with exemplar quotes.
• 7) Iterate with stakeholders: use Evidano's document chat to answer follow-ups and generate policy option memos.

The DfSIT 15 July 2026 report is a rich mixture of representative metrics and qualitative submissions, ideal for AI-enabled thematic and cross-segment research.

• Try a reproducible pilot: ingest the report's PDF and annex ODS files, run theme extraction, and produce a one-page decision brief in days, not weeks.
• Get started: Try Evidano for free or visit Evidano to discuss a pilot for your policy or research project.