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    <span class="logo-text">Data investigation suggests Russian attempts to influence the general election.</span>
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                    <h1 class="content-header-heading">Data investigation suggests Russian attempts to influence the general election.</h1>
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    <p class="news-item-summary">Swansea University academics working with in conjunction with The Sunday Times have conducted a data investigation which suggests that there were Russian attempts to influence the result of the 2017 general election.</p>

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        <p align="center" style="text-align: left;"><img src="/media/Web image.jpg"
alt="Twitter bots" title="Twitter bots" /></p>
<p align="center" style="text-align: left;">&nbsp;</p>
<p align="center" style="text-align: left;">&nbsp;</p>
<p align="center" style="text-align: left;">&nbsp;</p>
<p align="center" style="text-align: left;">&nbsp;</p>
<p align="center" style="text-align: left;">&nbsp;</p>
<p align="center" style="text-align: left;">&nbsp;</p>
<p align="center" style="text-align: left;">&nbsp;</p>
<p align="center" style="text-align: left;">&nbsp;</p>
<p align="center" style="text-align: left;">Using data collected from Twitter Streaming API, Professor Oleksandr Talavera and Tho Pham, the academic team from the University&rsquo;s&nbsp;<a href="http://www.swansea.ac.uk/som/" title="http://www.swansea.ac.uk/som/">School of Management</a>&nbsp;extracted a sample of 20,000 General Election-related tweets sent in the four weeks leading up to the vote by accounts which gave their language, location, or time zone as Russian. While the Twitter account&rsquo;s primary language is not usually clearly visible on a Twitter profile, the Swansea team were able to find the data that included that crucial detail. This sample was further explored by the Sunday Times, who examined each tweet by hand to determine whether they had posted positive or negative messages for any of the major parties</p>
<p align="center" style="text-align: left;"><strong>The findings</strong></p>
<p align="left">The analysis found that from the tweets that expressed a view on a party, the vast majority were pro-Labour or anti-Tory. Indeed nine out of ten messages expressing a view on Labour were positive and nine out of ten Conservative messages were negative. They were posted by 6,500 Russian accounts, the majority of which were clearly identifiable as automated accounts.</p>
<p align="left">The team were able to spot the bots because the vast majority were created simultaneously in huge batches in the months immediately leading up to the election. Their profiles were also in identical formats with English female names, random alphanumeric usernames of exactly 15 characters and Russian given as their primary language. Many tweeted exactly the same pro-Labour message in unison and have since either disappeared or been suspended by Twitter.</p>
<p align="left">Professor Talavera who led the research said: &ldquo;The scale of Russian interference is difficult to measure as the data is a very small sample of all general election-related Twitter activity, but the inference is that it is just &ldquo;the tip of the iceberg&rdquo;.</p>
<p align="left">&ldquo;Several of the same tactics used in Russian activity detected in the US election can be seen in this sample. Our data shows Russian accounts tweeted on election day to urge Labour supporters to vote. Prosecutors say they did exactly the same for Trump voters. Many of our Russian bot accounts gave American states as their location in exactly the same way as was seen in the US.&rdquo;</p>
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            <a href="/press-office/news-archive/2018/datainvestigationsuggestsrussianattemptstoinfluencethegeneralelection.php" rel="bookmark">
                <abbr class="published" title="2018-04-30T14:06:00+01:00">Monday 30 April 2018 14.06 BST</abbr>
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            <abbr class="updated" title="2018-04-30T13:09:24+01:00">Monday 30 April 2018 13.09 BST</abbr>
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