Evidence map›Paper›PMID 33706816›Full record

ArticlePublic health nutrition2021

A mixed-method analysis of the #SugarTax debate on Twitter.

Gemma Bridge, Stuart W Flint, Ralph Tench

Abstract read
In one paragraph

Article in Public health nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. An Analysis of Arguments Advanced via Twitter in an Advocacy Campaign to Promote Electronic Nicotine Delivery Systems.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2023
    Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Gemma BridgeLeeds Business School, Leeds Beckett University, LeedsLS1 3HB, UK.ORCID 0000-0001-7441-9849
Stuart W FlintSchool of Psychology, University of Leeds, LeedsLS2 9JT, UK.ORCID 0000-0003-4878-3019
Ralph TenchLeeds Business School, Leeds Beckett University, LeedsLS1 3HB, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the #SugarTax debate on Twitter to assess actors involved, their connections and the topics being discussed during the implementation and first anniversary of the UK Soft Drink Industry Levy.

designThe structure of the #SugarTax debate on Twitter was assessed using social network analysis. The actors involved, their connections and the topics of discussion taking place were also explored using content, sentiment and thematic analyses.

settingTwitter between 2017 and 2019.

participantsTwitter users engaging in discussions relating to the hashtag 'SugarTax'.

resultsTweets (n 5366) posted between 5 August 2017 and 7 May 2019 containing #SugarTax were downloaded from Twitter using Network Overview for Discovery and Exploration in Excel. The network included 1883 users, with 686 unique edges and 4679 edges with duplicates. The majority of tweets were negative in sentiment, when assessed by both automatic (64 %, n 141) and manual sentiment analysis (52 %, n 115) methods. Nine key themes were identified and grouped into two groups according to 'support for a sugar or SSB tax' or 'opposition for a sugar or SSB tax'.

conclusionsTwitter was used as a platform for debating the benefits and limitations of sugar-sweetened beverage taxes. The findings indicate that numerous actors are involved in the debates on Twitter, with advocates and lobbyists using the platform to raise support for their campaigns and reshape public perceptions. The findings and the methods used may be of interest to policymakers as well as to academics and members of the public looking to explore and engage in policy debates.

Indexed as

Social MediaSugar-Sweetened BeveragesCarbonated BeveragesHumansSugarsTaxesSugarsHealth policySocial mediaSocial network analysisSugar taxThematic analysis

Identifiers

PMID33706816
PMCPMC10195284

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.