Showing posts with label Twitter. Show all posts
Showing posts with label Twitter. Show all posts

Sunday, 22 December 2024

A role for qualitative methods in researching Twitter data on a popular science article's communication

Written for scholars and students who are interested in using qualitative research methods for research with small data, such as tweets on X.


Myself, Dr Corrie Uys, Dr Pat Harpur and Prof Izak van Zyl's open-access paper, 'A role for qualitative methods in researching Twitter data on a popular science article's communication' identifies several potential qualitative research contributions in analysing small data from microblogging communications:

 

Qualitative research can provide a rich contextual framing for how micro-practices (such as tweet shares for journal articles...) relate to important social dynamics (... like debates on paradigms within higher-level social strata in the Global Health Science field) plus professionals' related identity work. Also, in-depth explorations of microblogging data following qualitative methods can contribute to the research process by supporting meta-level critiques of missing data, (mis-) categorisations, and flawed automated (and manual) results.


Published in Frontiers in Research Metrics and Analytics journal's special topic, Network Analysis of Social Media Texts, our paper responds to calls from Big Data communication researchers for qualitative analysis of online science conversations to better explore their meaning. We identified a scholarly gap in the Science Communication field regarding the role that qualitative methods might play in researching small data regarding micro-bloggers' article communications. Although social media attention assists with academic article dissemination, qualitative research into related microblogging practices is scant. To support calls for the qualitative analysis of such communications, we provided a practical example:


Mixed methods were applied for better understanding an unorthodox, but popular, article (Diet, Diabetes Status, and Personal Experiences of Individuals with Type 2 diabetes Who Self-Selected and Followed a Low Carbohydrate High Fat diet) and its Twitter users' shares over two years. Big Data studies describe patterns in micro-bloggers' activities from large sets of data. In contrast, this small data set was analysed in NVivo™ by me (a pragmatist), and in MAXQDA™ by Corrie (a statistician). As part of the data preparation and cleaning, a comprehensive view of hyperlink sharing and conversations was developed, which quantitative extraction alone could not support. For example, through neglecting the general publication paths that fall outside listed academic publications, and related formal correspondence (such as academic letters, and sharing via open resources).


My multimodal content analysis found that links related to the article were largely shared by health professionals. Its popularity related to its position as a communication event within a longstanding debate in the Health Sciences. This issue arena sees an emergent Insulin Resistance (IR) paradigm contesting the dominant “cholesterol” model of chronic disease development. Health experts mostly shared this article, and their profiles reflected support for the emergent IR paradigm. We identified that these professionals followed a wider range of deliberation practices, than previously described by quantitative SciComm Twitter studies. Practices ranged from being included as part of a lecture-reading list, to language localisation in translating the article's title from English to Spanish, and study participants mentioning being involved. Contributing under their genuine identities, expert contributors carried the formal norms for civil communication into the scientific Twitter genre. There were no original URL shares from IR critics, suggesting how sharing evidence for an unconventional low-carbohydrate, healthy fats approach might be viewed as undermining orthodox identities. However, critics did respond with pro-social replies, and constructive criticism linked to the article's content, and its methodological limitations.

 

The statistician's semantic network analysis (SNA) confirmed that terms used by the article's tweeters related strongly to the article's content, and its discussion was pro-social. A few prominent IR individual advocates and organisations shared academic links to the article repeatedly, with its most influential tweeters and sharers being from England and South Africa. In using Atlas.ti and MAXQDA's tools for automated sentiment analysis, the statistician found many instances where sentiment was inaccurately described as negative when it should have been positive. This suggested a methodological limitation of quantitative approaches, such as QDAS, in (i) accurately analysing microblogging data. The SNA also uncovered concerns with (ii) incorrect automated counts for link shares. Concerns i & ii indicate how microblogging statistics may oversimplify complex categories, leading to inaccurate comparisons. In response, close readings of microblogging data present a distinct opportunity for meta-critique. Qualitative research can support critiques of microblogging data sources, as well as its use in QDAS. A lack of support for static Twitter data spreadsheet analysis was concerning.


Meta-inferences were then derived from the two methods' varied claims above. These findings flagged the importance of contextualising a health science article's sharing in relation to tweeters' professional identities and stances on what is healthy. In addition, meta-critiques spotlighted challenges with preparing accurate tweet data, and their analysis via qualitative data analysis software. Such findings suggest the valuable contributions that qualitative research can make to research with microblogging data in science communication.


The manuscript's development history

In 2020, Dr Pat Harpur and I selected an outlier IR scientific publication based on its unusually high Twitter popularity. At that time, the editorial, 'It is time to bust the myth of physical inactivity and obesity: you cannot outrun a bad diet' had been tweeted about over 3,000 times (now nearing 4,000 according to Altmetric!). However analysing this highly popular outlier stalled after its static export in qualitative data analysis software proved unsuitable for efficient coding. The large quantum of tweet data also proved very difficult to analyse. Accordingly, we shifted focus to a popular article that had been shared as an episode of a broader, long-running IR versus cholesterol debate. Even with its relatively small volume of tweets, organising this data for qualitative analysis proved challenging. For example, it was necessary to refine the Python extraction code, while cross-checks of static vs Twitter search results necessitated the capture of “missing” conversations.


We originally developed a multimodal analysis of these tweets, which focused on their relationship to Twitter user's profiles, potentially reflecting a wide range of communication goals. Our manuscript was submitted in 2022 to Science Communication, where Professor Susanna Priest kindly gave in-depth feedback on changing the original manuscript's contribution to a methodological one. We tackled this through developing a rationale for qualitative research with small data in the majorly revised article, which Dr Corrie Uys did a semantic network analysis for, while I revisited the social semiotic analysis.

If you have any questions, comments or concerns about our article, please comment below.


Acknowledgements

Funding is scarce, and often non-existent, for South African social media research projects. The article is the fifth in the Academic Free Speech and Digital Voices theme, thanks to The Noakes Foundation’s ongoing support. We appreciate Jana Retief and Jayne Bullen's assistance with related funding applications, plus the launch at Younglings Africa's Social Media Internet Laboratory for Research (SMILR) in 2019. The authors also appreciate the Cape Peninsula University of Technology and the Department of Higher Education for providing additional internal funding.

The authors would like to thank Younglings Africa's founder, Alwyn van Wyk, and all the SMILR project team members who assisted us: Shane Abrahams, Tia Demas, Scott Dennis, Ruan Erasmus, Paul Geddes, Sonwabile Langa, Russell MagayaJoshua Schell and Zander Swanepoel. In addition, we are grateful to the senior software data analysts, Cheryl Mitchell (2021-22) and Darryl Chetty (2019-20), who guided Younglings in their Twitter data extractions, and QDAS import preparations.

We also thank the Design and Research Activities Workgroup in CPUT's Faculty of Informatics and Design, plus the Centre for Communication Studies for feedback on our work-in-progress presentation in 2021.

P.S. Related research manuscript from the team

In reducing our manuscript’s word count, we cut a fair amount of content that we intend to use for our next collaboration: ‘Overcoming qualitative analysis challenges when using small data -  workarounds in exploring Twitter conversations’. Expressions-of-interest from journal editors are most welcome.

Tuesday, 26 September 2023

Noteworthy disparities with four CAQDAS tools: explorations in organising live Twitter (now known as X) data

Written for researchers interested in extracting live X (formerly Twitter) data via Qualitative Data Analysis Software tools

Social Science Computer Review (SSRC) has just published a paper by yours truly, Dr Pat Harpur and Dr Corrie Uys to https://doi.org/10.1177/08944393231204163. As the article's title suggests, we focus on the contrasting the Qualitative Data Analysis Software (QDAS) packages that currently support live Twitter data imports. 

QDAS tools that support live data extraction are a relatively recent innovation. At the time of our fieldwork, four prominent QDAS provided this: only ATLAS.ti™, NVivo™, MAXQDA™ and QDA Miner™ had Twitter data import functionalities. Little has been written concerning the research implications of differences between their functionalities, and how such disparities might contribute to contrasting analytical opportunities. Consequently, early-stage researchers may experience difficulties in choosing an apt QDAS to extract live data for Twitter academic research.
In response to both methodological gaps, we spent almost a year working on a software comparison to address the research question (RQ) 'How do QDAS packages differ in what they offer for live Twitter data research during the organisational stage of qualitative analysis?'. Comparing their possible disparities seems worthwhile since what QDAS cannot, or poorly, support may strongly impact researchers’ microblogging data, its organisation, and scholars’ potential findings. In the preliminary phase of research, we developed a features checklist for each package, based on their online manuals, product descriptions and forum feedback related to live Twitter imports. This checklist confirmed wide-ranging disparities between QDAS, which were not unexpected since they are priced very differently- ranging from $600 for an ATLAS.ti subscription, to $3,650 for a QDAMiner (as part of the Provalis Research’s ProSuite package, which also includes WordStat 10 & Simstat).

To ensure that each week's Twitter data extractions could produce much data for potential evaluation, we focused on extracting and organising communiqués from the national electrical company, the Electricity Supply Commission (Eskom). ‘Load-shedding’ is the Pan South African Language Board’s word of the year for 2022 (PanSALB, 2022), due to it most frequent use in credible print, broadcast and online media. Invented as a euphemism by Eskom’s public-relations team, load-shedding describes electricity blackouts. Since 2007, planned rolling blackouts have been used in a rotating schedule for periods ‘where short supply threatens the integrity of the grid’ (McGregor & Nuttall, 2013). In the weeks up to, and during, the researchers’ fieldwork, Eskom, and the different stages of loadshedding strongly trended on Twitter. These tweets reflected the depth of public disapproval, discontent, anger, frustration, and general concern.

QDAS packages commonly serve as tools that researchers can use for four broad activities in the qualitative analysis process (Gilbert, Jackson, & di Gregorio, 2014). These are (a) organising- coding sets, families and hyperlinking; (b) exploring - models, maps, networks, coding and text searches; (c) reflecting - through memoing, annotating and mapping; and (d) integrating qualitative data through memoing with hyperlinks and merging projects (Davidson & di Gregorio, 2011; Di Gregorio, 2010; Lewins & Silver, 2014).
Notwithstanding the contrasts in the costs for different QDAS packages, it was still surprising how much the QDAS tools varied for the first activity, (a) ‘organising data’ in our qualitative research project: Notably, the quantum of data extracted for the same query differed, largely due to contrasts in the types and amount of data that the four QDAS could extract. Variations in how each supported visual organisation and thematic analysis also shaped researchers’ opportunities for becoming familiar with Twitter users and their tweet content. 
Such disparities suggest that choosing a suitable QDAS for organising live Twitter data must dovetail with a researcher’s focus: ATLAS.ti accommodates scholars focused on wrangling unstructured data for personal meaning-making, while MAXQDA suits the mixed-methods researcher. QDA Miner’s easy-to-learn user interface suits a highly efficient implementation of methods, whilst NVivo supports relatively rapid analysis of tweet content.
We hope that these findings might help guide Twitter social science researchers and others in QDAS tool selection. Our research has suggested recommendations for these tools developers to follow for potentially improving the user experience for Twitter researchers. Future research might explore disparities in other qualitative research phases, or contrast data extraction routes for a variety of microblogging services.  More broadly,  an opportunity for a methodological contribution exists regarding research that can define a strong rationale for the software comparison method.
The authors greatly appreciate the SSRC's editor, Professor Stephen Lyon, advice on improving our final manuscript. We also thank The Noakes Foundation for its grant AFSDV02- our interdisciplinary software comparison would not have been possible without funding to cover subscriptions to the most extensive versions of MAXQDA Analytics Pro and QDA Miner. All authors are affiliated with the Cape Peninsula University of Technology (CPUT) and appreciate CPUT's provision of licensed versions of ATLAS.ti.

Please comment below if you have any questions or comments regarding our paper?

Thursday, 29 June 2023

Twitter Support must do better for helping celebrity and public victims of a global diet phishing scam!

Worldwide, diet scammers are marketing fake “endorsements” from celebrities across social media adverts, search engine ads and online content to phish victims’ financial details. The sheer volume of content the fraudsters produce is very difficult for celebrities and their representatives to tackle alone. One major obstacle to stopping the false marketing of “miracle weightloss products” is the reluctance of social media platforms to take down fake accounts and ads timeously. The fraudsters typically run the ads regionally for a few days in which they are displayed to hundreds of thousands of people. Just a fraction of an ad’s viewers need to share their financial details for the scam to be highly profitable!

This post presents the underwhelming example of reporting diet phishing accounts to Twitter Support as a way to spotlight the difficulties of tackling fraud via social media platforms. Hopefully publicly shaming @TwitterSupport will encourage its leaders to help address the global diet phishing scam properly, whilst also providing decent reporting options for celebrities and their representatives:

South African celebrities hijacked in fake diet adverts

A major factor in the “success" of this global scam (it has been running since 2014!) is the poor response from Facebook, Instagram, Twitter and other social media companies to formal requests to close fake accounts and their advertisement campaigns. Their ineffective responses are legally shortsighted: social media companies that repeatedly permit diet phishing ads on their platforms are complicit in a fraud, and possibly in the delict of passing off. For example, in South Africa, the diet phishing scam has undoubtedly harmed the reputation of Prof Tim Noakes and The Noakes Foundation through its fraudulent, direct misrepresentation, of fake products. These have certainly confused the public and @TheNoakesF has lost goodwill from the many victims of the fraud’s misrepresentation! 

Prof Noakes, is just one of many well-known individuals whose identities have been hijacked. The South African version of the scam has seen: Minki van der Westhuizen, Jeannie D (@Jeannieous), Basetsana Kumalo (@basetsanakumalo), Nkhensani Nkosi (@NkhensaniNkosi1), Shashi Naidoo (@SHASHINAIDOO), Tumi Morake (@tumi_morake), Dawn King (@DawnTKing), Ina Parmaan (@inapaarman) and Dr Shabir Madhi (@ShabirMadh) all having their reputations tarnished.

Since Prof Noakes’ identity was first hijacked in 2020, The Noakes Foundation (TNF) and partners (such as Dr Michael Mol and Hello Doctor) have tried many options to stop the scam. For example, TNF developed and publicised content against it via blogposts, such as Keto Extreme Scams Social Media Users Out of Thousands. TNF also produced these videos: Professor Tim Noakes vs. Diet Phishing: Exposing a Global Scam with Fake Celebrity Endorsements, Dr Michael Mol highlighting Diet Scams and Prof Noakes Speaks Out Against The Ongoing Diet Scam. Sadly, The Noakes Foundation’s repeated warnings to the public don’t seem to be making much difference in preventing new victims!

American, Australian, British and Swedish celebs hijacked, too!

In the United States, the diet phishing scam has also stolen the identities of major celebrities. Most are in popular TV franchises: Oprah Winfrey (@Oprah), Dr Mehmet Oz (@DrOz) Dr Phil (@DrPhil), Dolly Parton (@DollyParton), Kelly Clarkson (@kellyclarkson), the Kardashian Family (@kardashianshulu + @KimKardashian), Kelly Osbourne (@KellyOsbourne), Chrissy Teigen (@chrissyteigen), Martha Maccallum (@marthamaccallum), Blake Shelton (@blakeshelton) and #TomSelleck 🥸. It’s a Magnum opus of fraud!

Amazing female celebs in the United Kingdom have also seen their identities stolen. Diet phishing scammers have hijacked the IDs of Holly Willis (@hollywills), Amanda Holden (@AmandaHolden), Anne Hegerty (@anne_hegerty) and Dawn French (@Dawn_French). Even the British (@RoyalFamily) has not been immune, with the targeting of Catherine, the Princess of Wales (@KensingtonRoyal) and the Former Queen Elisabeth II, RIP and God Bless. Sadly, Meghan Duchess of Sussex, has been targeted too...

Down Under, well-known Australian personalities, such as its national treasure Maggie Beer (@maggie_beer) and Farmer Wants A Wife host Sam Armytage (@sam_armytage) have had their identities misused for fake #weightloss endorsements. And also Mr Embarrassing Bodies Down Under himself, Dr Brad McKay (@DrBradMcKay).

In Sweden, Dr Andreas Eenfeldt (@DrEenfeldt from @DietDoctor), another leader in the low carbohydrate movement, has been targeted in promotions of fake #keto products. Sadly, the fake ads seem to generate far more attention and action than his or my father's health advice!

N.B. The examples above are not extensive in terms of all victims. We largely know of celebrities in the Anglosphere whose identities were stolen, then featured in English language reports and related search engine results.


Deceptive "Tim Noakes" Twitter accounts market Keto Gummies

Just as the celebrity names stolen for the fake ads change often, so do the product names. A few examples of these fake names are Capsaicin, FigurWeightLossCapsules, Garcinia, Ketovatru and KetoLifePlus. Be warned that new "products" are added every month! One particularly common term used in the scammers'  product names is "Keto Gummies". A recent Twitter search for "Tim Noakes keto gummies" suggested many fake accounts in Figure 1 (just the top view!), plus diverse "product" names.




Figure 1. Twitter search results for Tim Noakes keto gummies (fake product accounts) (20 June, 2023)



Twitter Support does not think fake accounts are misleading and deceptive?!

These accounts have clearly been setup to fraudulently market "keto gummies" by suggesting an  association with "Tim Noakes". So, the logical response for any representative of The Noakes Foundation would seem to be reporting each fake account for violating Twitter’s misleading and deceptive identities policy, right?



Figure 2. Reporting the fake Tim Noakes Keto Gummies account to Twitter support

This is a very time consuming process- in the first place, the same complaint must be individually submitted for each account. Secondly, the representative reporting these complaints must also upload and/or email related proof of ID, business and legal documentation to Twitter Support before it will consider investigating whether impersonation is taking place.

Fake Twitter accounts, including those below, were reported to Twitter, with support documentation:
@NoakesGumm28693 0327118996     @TimNoakesHoax 0327120384
@TimGummies 0327119602                 @NoakesGumm91126 0327119675
@gummies_tim 0327120030                 @TimNoakes_ZA 0327119741
@tim_gummies 0327118910                 @NoakesSouth 0327118634
@timnoakesketo0 0327119362              @NoakesGumm22663 0327119487

In each case, @TwitterSupport replied that the following accounts are NOT in violation of Twitter’s misleading and deceptive identities policy. This would seem to contradict the obvious evidence that Tim Noakes' name has been hijacked by scammers for misleading victims with a fake product!

The Noakes Foundation has supplied its legal team with Twitter's related correspondence for review. I will update this post as developments progress (or fail to!) with the remarkably unhelpful and potentially criminally negligent @TwitterSupport.

This "Tim Noakes keto gummies" Twitter account is not deceptive?!

Figure 3. Fake @TimNoakesKetoGummies account

Figure 3. Fake @TimNoakesKetoGummies account
 
Figure 3 shows a typical example of a fake account's style. It uses Tim Noakes' name, plus stock photography in marketing a non-existent product. It only tweeted on May the 24th, and is followed by one person. Any knowledgeable complaint reviewer would surely consider this to be a case of a scammer creating a misleading and deceptive account for gaming Twitter's search engine. However, Twitter Support does not agree, nor explain why in its generic correspondence around each scam account.

From stealing victims' banking details to delivering dubious products

As fitness expert Reggie Wilson (@fitforfreelance) deftly explains in his 30 second video, Keto Gummies cannot work. It is most concerning that The Noakes Foundation has received reports that scammers are now delivering a physical product to South African victims. Not only are fake #KetoGummies products being marketed locally via takealot.com BUT are also offered internationally via Amazon.com, and possibly other major online retailers!

Just as the scammers link themselves to celebs on Twitter, they also target the popular television franchises they're from. Notably: AmericasNextTopModel, DragonsDen, The Kardashians, The Oprah Show and Shark Tank. On Twitter, national businesses are also being misrepresented as selling these fake products, such as Walmart in the US, Jean Coutu pharmacies in Canada and Dischem in South Africa. Type in keto gummies into these retailers search engines and you will see that many options pop up, some seemingly associated with popular celebrities and TV franchises.

The Noakes Foundation is keen to work with affected celebrities, their representatives and business to raise the pressure on social media companies to make a proper response to the scammers and fake ads they host. Do let us know if you would like to help using the comments below, or by emailing reportdietscam@gmail.com.

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