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Social Sense

Open data · analytics.db

Every number on this site, as tables

The app reads a single read-only SQLite file built by scripts/build_analytics.py. It holds 19 tables and 15,828 rows of aggregates: counts and score sums, official statistics and boundary metadata. No tweet or toot text, user names or ids are stored.

Tables

Browse the database

Scenarios

  • Scenario 1: income vs sentiment

    scenario_income_sa2

    457 rows

    Median income joined with suburb tweet sentiment pooled to each Victorian SA2 (revival analysis). avg_* are NULL where an SA2 had no tweets.

    10 columns CSV

  • Scenario 2: crime vs sentiment

    scenario_crime_lga

    79 rows

    Offence totals joined with suburb tweet sentiment pooled to each Victorian LGA (revival analysis).

    9 columns CSV

  • Scenario correlations

    scenario_correlations

    19 rows

    Pearson, Spearman and least-squares fits at several minimum-tweet thresholds (computed with scipy).

    14 columns CSV

Sentiment

  • Sentiment histograms (2023 dashboard)

    sentiment_histogram

    81 rows

    Counts of 1-9 sentiment scores for Twitter and the three Mastodon servers, as plotted in 2023. Twitter covers geotagged tweets Australia-wide, Feb-Jul 2022.

    4 columns CSV

  • Twitter sentiment by suburb (SAL)

    twitter_sal_sentiment

    6,799 rows

    CouchDB MapReduce _stats per suburb and topic (all tweets, income keywords, crime keywords), Feb-Jul 2022, every Australian state. Rows are keyed by SAL code: join regions_sal for names.

    9 columns CSV

  • Mastodon servers

    mastodon_servers

    3 rows

    The three servers the harvesters followed.

    4 columns CSV

  • mastodon.social re-scored histogram

    mastodon_rescored_histogram

    27 rows

    The surviving week of mastodon.social toots (1-9 May 2023) re-scored with the original pipeline (aggregates only).

    4 columns CSV

  • mastodon.social by hour

    mastodon_hourly

    144 rows

    Re-scored mastodon.social toots per UTC hour, 1-9 May 2023, with score sums and 1-9 bucket counts.

    16 columns CSV

  • mastodon.social by language

    mastodon_language

    112 rows

    Re-scored mastodon.social toots (1-9 May 2023) per declared language, with score sums and bucket counts.

    14 columns CSV

SUDO

  • Personal income by SA2

    income_sa2

    2,234 rows

    SUDO / ABS personal income 2015-16 (mean, median, sum, median age of earners) for every Australian SA2.

    13 columns CSV

  • Personal income by capital city area

    income_gcc

    15 rows

    The SA2 rows grouped by Greater Capital City Statistical Area, as in the original summary.

    7 columns CSV

  • Jobs and income by industry

    jobs_income_indicators

    40 rows

    ABS Jobs in Australia 2018-19 indicators (mean, sd and median across SA2s) from the original bar chart.

    6 columns CSV

  • Recorded offences by LGA

    crime_lga

    79 rows

    Victorian Crime Statistics Agency offence divisions per LGA (reference year 2019).

    11 columns CSV

Geography

Context

  • Facts

    facts

    18 rows

    Headline numbers quoted in the team report, each with its source section.

    4 columns CSV

  • Build metadata

    meta

    7 rows

    Editions of the boundaries and how the database was built.

    2 columns CSV

  • Original summaries

    summary_text

    17 rows

    The paragraphs the 2023 dashboard showed beside each chart (written by the team).

    4 columns CSV

Provenance and licences: Twitter aggregates derive from the University-provided corpus (Australian Data Observatory); SUDO income and offence figures are ABS and Crime Statistics Agency Victoria data; ABS boundaries are CC BY 4.0. The whole file is in the repository at web/data/analytics.db and can be opened with any SQLite browser.