Third of gold sold on Amazon and eBay could be fake – how to spot it
MORE than a third of “gold” jewellery sold on websites such as Amazon and eBay could be fake.
Out of 17,657 online gold listings checked over a 10-day period, 6,377 of them weren’t advertised as hallmarked, a study has found.
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More than a third of gold sold online could be fake, a study has foundCredit: Getty – Contributor
It is illegal to sell anything in the UK made from a precious metal, silver, gold, platinum and palladium, over a certain weight without a hallmark, which confirms the material.
The regulation was put in place to protect consumers and retail jewellers, but it doesn’t apply to listings at online retailers meaning consumers could be “duped”, the British Hallmarking Council and Goldsmiths’ Company Assay Office have warned.
Of the listings with no hallmark, 4,278 of all items were suspected as fake and are therefore being sold illegally, according to its data.
Overall, eBay sellers alone accounted for 56 per cent of all suspect items of “gold” jewellery being sold online, where there was no mention of a hallmark.
How to verify gold jewellery’s authenticity
BELOW are some tips from the Goldsmiths’ Company Assay Office on how to make sure your jewellery is legit.
- Always check for a hallmark: This is the consumers’ guarantee. You would need to check the listing and the picture of the item
- If in doubt ask: If you can’t see any, you should ask the seller if an item has been hallmarked and for evidence to prove it before you buy
- Check the price: If it seems too good to be true, that’s because it probably is
If you think you’ve been sold fake gold you should speak to Citizens Advice, which can give advice to help resolve a dispute.
The research suggested there could be around 150,000 items of fake gold jewellery listed for sale online in the UK each year.
British Hallmarking Council chairman Noel Hunter said: “The UK Hallmarking Act was put in place to protect consumers and retail jewellers from counterfeits, but the application of the legislation to online trading activity remains untested.
“And we have seen little appetite from the internet giants to step up enforcement or adequately protect consumers.
“Our internet sweep highlights just a fraction of the infringements made by online sellers of ‘precious metal jewellery’ in the UK today.”
Robert Organ, deputy warden for the Goldsmiths’ Company Assay Office, said: “We are calling on the government to work with us and the other assay offices in the UK to develop a robust enforcement strategy that protects consumers and businesses from internet based, unfair trading practices.
“This must include a review of the current Hallmarking Act to see if it could be extended to cover internet trade.
“We are also asking the Government to work with Amazon and eBay to increase hallmarking information on precious metal jewellery listings, raising consumer and seller awareness about hallmarking and the law.”
An Amazon spokesperson told The Sun: “Selling partners are required to comply with all relevant laws and regulations when listing items for sale in our stores.
“Those who do not will be subject to action, including removal of selling privileges and withholding of funds.”
The Sun also contacted eBay for a comment.
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Earlier this year, a homeless man found £10,000 of gold and jewellery in the street and handed it in saying “I don’t worship money”.
A few years ago, deals website Groupon was accused of “conning shoppers by flogging fake gold jewellery”.
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Researchers develop AI that distinguishes between satire and fake news
How can you distinguish between satire and fake news? It usually comes down to semantic and linguistic differences, but the nuances can be tough to spot. That’s why researchers at George Washington University, Amazon AWS AI, and startup AdVerifai investigated a machine learning approach to classifying misleading speech. They say the AI model they developed, which outperformed the baseline, lays the groundwork for the study of additional linguistic features.
Their work follows that of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), which earlier this year architected an AI model that could determine whether a source is accurate or politically prejudiced. In subsequent work, MIT CSAIL used one of the world’s largest fact-checking data sets to develop automated systems that could detect false statements.
The paper’s coauthors note that efforts to reduce the spread of misinformation have occasionally resulted in the flagging of legitimate satire, particularly on social media. Complicating matters, some fake news purveyors have begun masquerading as satire sites. These developments of course threaten the business of legitimate publishers, which might struggle to monetize their satire, but also they affect the experience of consumers, who could miss out on miscategorized content.
The researchers hypothesized that metrics of text coherence might be useful in capturing semantic relatedness between sentences of a story. To this end, they used a set of indices related to text statistics implemented by Coh-Metrix, a tool for producing linguistic and discourse representations. There were 108 in total, including (but not limited to) the number of words and sentences; referential cohesion, which refers to overlap in content words between sentences; various text readability formulas; and different types of connective words.
The researchers leveraged a statistical technique called principal component analysis to convert potentially correlated metrics into uncorrelated variables (or principal components), which they used in two logistic regression models (functions that model the probability of certain classes) with the fake and satire labels their dependent variables. Next, they evaluated the models’ performance on a corpus containing 283 fake news stories and 203 satirical stories that had been verified by hand.
The team reports that a classifier trained on the “significant” indices outperformed the baseline F1 score, a measure of the frequency of false positives and negatives. The top-performing algorithm achieved a 0.78 score, where 1 is perfect, while revealing that satirical articles tended to be more sophisticated (and less easy to read) than fake news articles.
In future work, the researchers plan to study linguistic cues such as absurdity, incongruity, and other humor-related features.
“Overall, our contributions, with the improved classification accuracy and toward the understanding of nuances between fake news and satire, carry great implications with regard to the delicate balance of fighting misinformation while protecting free speech,” they wrote.