FreshNetworks Blog: Top five posts in June


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As a social media agencyFreshNetworks aims to bring you the best posts in social media, online communities, marketing and customer engagement online. In case you missed them, find below our top five posts in June.

1. Social media monitoring review 2010 – download the final report

Over the first few months of 2010 we conducted an in-depth review of the leading social media monitoring tools in conjunction with our sister company, FreshMinds Research. We compared how Alterian, Brandwatch, Biz360, Neilsen Buzzmetrics, Radian6, Scoutlabs and Sysomos performed when monitoring conversations about global coffee brand Starbucks, analysing over 19,000 online conversations.

Many thousands of you have already read our posts about the review and downloaded the final whitepaper. If you haven’t yet, you can find a more detailed analysis of all these tools and more in our final report – Turning Conversations into Insights: a Comparison of Social Media Monitoring Tools.

2. Why a museum is the UK’s top brand on Twitter

The Famecount dataset is, like much data, not perfect but it does highlight some surprises that we can all learn from. The brand it has as the top Twitter brand in the UK is one such surprise. Rather than the big FMCG, fashion and media firms they include in their brands ranking, the top UK brand on Twitter for them is a museum, @Tate.

There are some structural reasons why the Tate will attract followers. Twitter is great for events and experiences and a museum has lots of these. But the success and popularity of the Tate is about much more than this. It’s thanks to the way they use Twitter. In this post we look at the three simple characteristics of the way the Tate uses Twitter that all brands can learn from, and that contribute to their success.

3. The most beautiful tweet ever written (as judged by @stephenfry)

In June, Stephen Fry declared the most beautiful Tweet ever written at the Hay Festival. The winning tweet, from Marc MacKenzie, is a concise but informative tweet and perhaps is a great example of how people are using this new medium. But what makes this tweet the most beautiful ever written?

The beauty in Twitter, and in the tweets people send, is that they convey emotion, opinion, information and expression in a relatively short period, and they, broadly speaking, do so in public. Unlike other conversational forms, Twitter, even when you direct a tweet at a specific person, has a broader audience and often an audience you don’t know. And of course you only have 14o characters with which to express yourself. Marc MacKenzie’s tweet is a good example of this new medium – the audience is unclear and the tweet manages to convey information, opinion, belief and also humour. All in 140 characters.

4. The top ten brands on Facebook

Starbucks is the most popular brand on Facebook when ranked by the number of people who ‘Like’ a brand (’Fans’ as they used to be called). Over 7.5 million people like the coffee chain on Facebook, almost 2 million more than like the second most popular brand, Coca-Cola.

This data comes from Famecount which ranks brands (and people) based on the number of people who follow, like or friend them in social networks. It shows that food and drink brands are in each of the top five places, with fashion brands making up most of the remaining places in the top ten. Consumers are interested in what these brands are doing, or at least want to flag their interest in the brand or product on their own Facebook profile.

5. The problem with automated sentiment analysis

As part of our review of social media monitoring tools we compared their automated sentiment analysis with the findings of a human analyst, looking at seven of the leading social media monitoring tools – Alterian, Brandwatch, Biz360, Neilsen Buzzmetrics, Radian6, Scoutlabs and Sysomos. And the outcome suggests that automated sentiment analysis cannot be trusted to accurately reflect and report on the sentiment of conversations online.

In our tests when comparing with a human analyst, the tools were typically about 30% accurate at deciding if a statement was positive or negative. In one case the accuracy was as low as 7% and the best tool was still only 48% accurate when compared to a human. For any brand looking to use social media monitoring to help them interact with and respond to positive or negative comments this is disastrous. More often than not, a positive comment will be classified as negative or vice-versa. In fact no tool managed to get all the positive statements correctly classified. And no tool got all the negative statements right either. Automated sentiment does not work, and for businesses relying on it can cause problems.


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