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Extracting Context

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  • 1. 01/10/2010
    Extracting meaning from Social Media Monitoring
    ….OR
  • 2. 01/10/2010
    2
  • 3. Is they often present you with this...
    01/10/2010
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  • 4. Understanding the meaning of results and how to use monitoring tools so they work for you
    Filtering the information
    Using a top down approach to filtering often wastes time, money and effort
    Try a bottom up approach to define filters - it’s quicker and it will help understand the nature of the social media and how your brand interacts with it better - particularly useful when you need to ‘expand’ the search
    Use as many specifics as you can ( that may be none, but usually isn’t)
    Be prepared to spend some time planning how you will use filters to categorize and quantify data (every hour you spend at the planning stage can save you days in execution - and can be especially valuable when you are briefing vendors)
    Make sure the filters make sense to your business and monitoring objectives
    01/10/2010
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  • 5. 01/10/2010
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    The perfect tool?
  • 6. How much do you already know about your audience?
    Take the time to establish which social media channels it makes sense for your audience to use
    Better still, choose a tool which allows you to check your assumptions
    Experiment and test your assumptions before you go setting up a whole lot of details in specifications and filtering
    Use ‘exceptions’ to exclude unwanted audiences
    Make sure you understand the vocabulary your audiences use
    01/10/2010
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  • 7. 01/10/2010
    7
    Data Cleanup
    The problem with social media is that finding 20,000 ‘hits’ is a lot easier than finding the 50 that matter
    Filters and exclusions can screen out obvious mismatches but can also cause you to ‘miss’ important items
    A successful strategy for cleaning data without losing integrity should include:
    Contextual matches rather than keywords
    Non-linguistic cues and vocabulary
    Links and associations (especially where you can set limits/minimum values)
    Use of active terms
    Use of specialized tags and terms to allow easier identification of who is responding to your brands content
    Incorporation of SEO terms used in materials designed for audiences
    Links outside social media groups for source and destination tagging
  • 8. Customizing the sample
    The first rule of data sampling should be: design backwards from the intended result/audience for your results”
    Establish what you are going to do with results
    Who are the ultimate recipients
    Do results have be consistent with other business functions’ results
    Don’t generate information no one can use ( i.e. if you are monitoring in real time - make sure there are real time processes which uses these results
    Question outside your own immediate needs – are you monitoring for research, evaluation, discovery, actionable insight, immediate response?
    Make sure your ‘cleaned data’ can be transformed into all the outlets and reports you require
    01/10/2010
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  • 9. A matter of Perspective
    Perspectives are a quick and easy way of overcoming one of the most persistent problems with analyzers - making the answer relevant to you.
    In data cleanup they can be used to eliminate a lot of irrelevant content
    In research they can be used to shift the view between , say, competing brands or topics
    Most analysers use people to add the perspective....
    ...but there is an alternative
    Automated perspectives can be specified as part of the filtering and cleanup process
    ‘stored perspectives’ allow a rapid comparison of data from different viewpoints which multiplies the business/media intelligence in the sample
    Anything automated can be switched on or off and can be modified
    Consistency in results will go up
    01/10/2010
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  • 10. Context
    Most sentiment analysers do not allow or imply context in their results
    which is why the results often don’t look right
    Context uses perspectives and filters to provide a means of matching the results to the brand or person relating to the monitoring objective
    Put simply - the results should make sense
    Context also allows the focus of monitoring to reflect actual process in a business e.g. A ‘buy’ decision or an expression of discontent about a service
    The role of context is to make ‘You’ the focus of the answer
    01/10/2010
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  • 11. Framing Questions
    The most important rule is to make sure the answers are answering YOUR questions
    Either make sure you test ‘logical’ questions ahead of time
    or......
    01/10/2010
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  • 12. An end to Keywords?
    Look at the new generation of analyzers which combine natural language and context to generate results which ‘mean’ what you ‘said’ in your question
    The benefit is that missed ‘hits’ are minimised simply because your vocabulary missed a word or variation, or the time tense is different, or one or more of the key elements isn’t language (such as an emoticon, or slang expressions
    This approach allows you to work in a more natural way in both framing questions and evaluating outcomes
    01/10/2010
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  • 13. The trouble with automated sentiment analysis
    Is often what it is expected to accomplish
    If you have designed in the filtering, contextual mapping and the end user of the information it is perfectly practical to expect a result in the 90-95% accuracy range
    Beware of claims over 95% (in a ‘live’ language, subject to fashion and the re-use of terms in new ways there are very real and tangible barriers
    But don’t make the mistake of assuming a human reader can do any better - a 2009 study of 2,000 people saw them score an average of 84% - and 88% was the top mark
    There is a ‘semantic’ trap’ in most analysers in that they use language as it is defined - not as it is actually used - and most rely on words (social media posters sometimes don’t) - a lot of language isn’t traditional linguistics!
    Black box solutions, however good they appear, are hiding things from you - insist on transparency
    01/10/2010
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  • 14. Death to all humans?
    01/10/2010
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  • 15. Why automated analysis is NOT about replacing people
    The role of automation is not about replacing people from the process – rather is should be about allowing you more time to think about what is important rather than speed reading
    Take the Apple iPhone 4 - social media DISCUSSION THREADS not posts were ruining at 30/second during the launch day - leaving anyone trying to read and make sense of the sentiment in a passive, or reactive state.
    This is an extreme, but most social media sites can easily overwhelm a human-based system allowing people to do little more than skim content
    Context- based analysis can reduce the results to actions and insights which are both manageable and insightful - without increasing the errors from volume - without getting tired and it will read every blog or post all the way through.
    01/10/2010
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  • 16. Making results count
    AVE? ROI? If you are going to be subject to externally generated measures (often for historical or consistency reasons) make sure you can measure something meaningful for the purpose
    Better still develop a metric which actually makes sense for what you are doing and communicate its benefits
    Make sure your results are not siloed to just social media - there are often links to other media forms (including your own materials) – make sure your solution integrates them all and can show you these relationships
    Dashboards:
    Employ ways of making your results and their context stand out – dashboards are both an excellent way of compressing complex information and adding impact to results (but too often are generalized templates presented by vendors – make sure you get what you want – how you want it)
    Can be used to extend your information into other parts of the business
    Can create synergy with other business processes - make sure your social media dashboard can take on information from other functions
    Don’t misuse dashboards to create meaningless measurements or introduce concepts which make no sense to anyone other than the graphics/metrics person who designed it - stick to what you know and can understand
    01/10/2010
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  • 17. And finally....
    Feedback loops – both in the human and automated sense are a valuable mechanism to ‘shrink wrap’ results ever closer to you brand objectives - use them!
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