{"id":1221,"date":"2025-05-05T08:54:41","date_gmt":"2025-05-05T08:54:41","guid":{"rendered":"https:\/\/edmohub.ie\/?page_id=1221"},"modified":"2025-05-05T09:52:30","modified_gmt":"2025-05-05T09:52:30","slug":"be-online-smart","status":"publish","type":"page","link":"https:\/\/edmohub.ie\/index.php\/be-online-smart\/","title":{"rendered":"Be Online Smart"},"content":{"rendered":"\n

Be Online Smart is a campaign by the European Digital Media Observatory (EDMO) and its network of 14 national hubs. It aims to raise awareness about how recommendation algorithms shape our online experience \u2014 from the news we read to the videos we watch. <\/p>\n\n\n\n

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Recommendation systems help us discover content we enjoy, but they can also limit what we see, amplify disinformation and extremism, and reinforce bias. <\/p>\n\n\n\n

A DCU study has shown<\/a> that social media algorithms rapidly push misogynistic and male supremacist content to users \u2014 often within minutes. Researchers created fake male accounts on YouTube Shorts and TikTok, and found they were quickly flooded with anti-feminist and extremist material, even without searching for it. <\/p>\n\n\n\n

The findings have fuelled growing calls for stricter regulation of recommendation systems, with new research from ICCL and Uplift showing that 74% of the Irish public want tougher controls<\/a>. ICCL has also criticised Ireland\u2019s national disinformation strategy<\/a> for ignoring the role of these powerful algorithms.<\/p>\n\n\n\n

Media literacy alone can\u2019t fix the problems of digital technology, but knowing how recommendation algorithms work is key to taking control online and joining the debate. The more we understand how algorithms shape what we see, the better we can spot misinformation, make informed choices, and stay in charge of our digital lives.<\/p>\n\n\n\n

Understanding recommendation algorithms<\/strong><\/p>\n\n\n\n

An algorithm<\/strong> is a set of instructions that tells a computer how to complete a task \u2014 the basic building blocks behind everything from apps to websites. The internet runs on algorithms: they filter spam in your email, rank results on Google, decide what posts you see on Instagram or TikTok, and shape the ads and products shown to you online.<\/p>\n\n\n\n

But many of these algorithms are proprietary, meaning we don\u2019t know exactly how they work or what they prioritise \u2014 even though they influence what we see, think about, and buy every day.<\/p>\n\n\n\n

Recommendation algorithms <\/strong>track what you do online and use that information to keep you engaged. Recommendation algorithms can be useful because they help us discover content we might like such as suggesting a new video, product, or playlist based on our interests or past activity. They save time and personalise our online experience.<\/p>\n\n\n\n

But they\u2019re also problematic because they often prioritise content that is sensational, emotional, or polarising<\/strong> rather than what\u2019s most accurate or helpful. On top of that, platforms can insert content they want you to see,<\/strong> including ads or sponsored posts paid for by others. So what shows up in your feed isn\u2019t always what you chose \u2014 it\u2019s often what someone else wants you to see.<\/p>\n\n\n\n

These algorithms lack transparency, so we don\u2019t know exactly how they work or why certain posts are shown to us. This can lead to misinformation, reinforce bias, and limit the diversity of information we see.<\/p>\n\n\n\n

So what can you do? <\/strong><\/p>\n\n\n\n

STOP<\/strong><\/p>\n\n\n\n

Don\u2019t believe something just because it\u2019s going viral.<\/p>\n\n\n\n

THINK<\/strong><\/p>\n\n\n\n

Read the whole story rather than just looking at the headlines on social media <\/p>\n\n\n\n

Remember that algorithms are often programmed to show you content you want to see.<\/p>\n\n\n\n

Question the algorithm: think about what is being represented, and what is being left out<\/p>\n\n\n\n

CHECK<\/strong><\/p>\n\n\n\n

Look for multiple sources and learn to find ones you trust.<\/p>\n\n\n\n

LEARN<\/strong><\/p>\n\n\n\n

Learn more about how algorithms work (and don\u2019t work)
Some suggestions:<\/p>\n\n\n\n