Mapping, planning, measuring
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The document discusses Dr. Stephen Dann's presentation on mapping, planning, and measuring social media conversations, focusing primarily on Twitter. It outlines a structured methodology for categorizing tweets and analyzing their content, emphasizing the importance of understanding the types of interactions that occur on social platforms. Key categories include conversational, news events, pass along, phatic, status, and spam, which help users effectively engage and measure their online presence.
Mapping, planning, measuring
- 1. ACT Mapping, Planning and Measuring Conversation The Twitter (Plus Others) Case Study June 2012 Dr Stephen Dann | @stephendann @stephendann
- 2. First, the house rules Fire up the technology Laptops open… tablets to hand… atomic batteries to power… smartphones to speed… #priapdp – today’s official hashtag @stephendann
- 3. Who am I? ANU Senior Lecturer If it’s marketing, I teach it* ANZMAC Webmaster www.anzmac.org Author eMarketing (2010), Palgrave UK Geek Brony, Nerf Player, Internet Addict * Nine different subject areas so far @stephendann
- 4. Where am I? Twitter Facebook YouTube Tumblr Instagram Soundcloud Slideshare Stephendann.net (HTML, Web1.0) Stephendann.com (Archive on a blog) @stephendann
- 5. What I do with the internet Write books about eMarketing An excuse to buy an Xbox, iPad, Wii, and play Facebook games as homework Publish research Twitter Paper (2010) Educate Classroom blogs, classroom twitter accounts @stephendann
- 6. What I do with the Internet Twitter @stephendann Personal account. Opinions, whims and friends @drstephendann Conference Play by Play commentator @mktg3024 Between class lecture theatre / tutorial room @anzmac Text based megaphone. Tweeting Since: 13/3/2007 (5 years, 3 months, 11 days) @stephendann
- 7. Phase 1 MAPPING @stephendann
- 8. So where does social media fit into the game plan? @stephendann
- 9. Where does social media fit? Those who were at Others the Twitter session… On your own answer Throw me a suggestion cards via @stephendann We’ll do the voice Don’t forget the #priapdp hashtag thing in a moment… @stephendann
- 10. Finding the fit Sales lead generation? Talkback radio? Market Research? Text based telephone? Two way radio? Pretending to be a cat? News ticker? Information hydration? Conversations? Pretending to be PM? @stephendann
- 11. With that in mind… Time for me to hold the stage for a moment @stephendann
- 12. Twitter Content Classification Project started in 2009, and is ongoing… 12000+ tweets coded… Peer reviewed and published • Academy of Marketing Science for the method • ANZMAC for the categories • First Monday as an open source methodology • Social Marketing in Public Health for the application • AMSRS conference for the measurement @stephendann
- 13. Why Twitter? This started as a rebutal to the Pear Analytics “Mostly Babble” statement about twitter. Twitter data is really easy to download Or I’m good at getting hold of Twitter data I like Twitter. @stephendann
- 14. What it was… A measurement system to track how people used their accounts 1. Acquire the timeline 2. Count the tweets (n) 3. Divide the tweets into one of six categories 4. Within those six categories, further subdivide into the specialist categories. 5. Calculate the % of tweets for each of the 28 possible options 6. Produce a scorecard. @stephendann
- 15. What it’s become Categories of conversation measure the output and Guide the output Not limited to Twitter Just founded and grounded there. @stephendann
- 16. Phase 2 PLANNING: THE CATEGORIES @stephendann
- 17. The Categories Conversational Spam News Events Status Pass Along Phatic @stephendann
- 18. Conversational Talking with the customer • Action • Activities involving other users • Group check in Conversational • Query • Questions, question marks or polls • Referral • An @response/reply/wall post which contains URLs or recommendation of other users. • Response • Catch-all classification for conversation @tweets • Replies in any social media context @stephendann
- 19. News Events: Telling the story • Announcement • Announcement of a forthcoming event • Hashtagged News Events • Participation in a live #tagged event • Headlines • personal eye-witness accounts of news events • Citizen journalism • Sport • Identifiable results of sporting events • Discussion of live sport from an event @stephendann
- 20. News Events: Telling the story • Natural Disaster • personal eye-witness of catastrophic weather events • Citizen weather bureau News Events • Transport • Roads, rail, public transport or flights • Weather • Report of prevailing weather conditions • Not just small talk @stephendann
- 21. Pass along: Share and share-alike • Automated Endorsement • Software triggered events Pass Along • Endorsement • links to content of interest • Secondary Social Media • Link from one service to another • User generated content • Links to own content Load out @stephendann
- 22. Phatic • Broadcast • Statements of opinion Phatic • Fourth wall • comments made directly to camera • Greetings • connections with the audience • Unclassifiable • Cat + keyboard = asfab w4 @stephendann
- 23. Status • Activity • answering “What are you doing now?” Status • Automated • triggered by third party applications • Location • answering “Where are you?” • Mechanical • any form of technology or mechanical systems Complaining about MS Word counts as mechanical @stephendann
- 24. Status • Personal • Answering “What are you feeling?” Status • Physical • Answering “What are you physically experiencing?” • Temporal • Answering “when are you?” • Work • Anything that relates to work. Why do people never get promoted for tweeting about work? @stephendann
- 25. Spam Really try not to be in this category. @stephendann
- 26. Spam • Administered Malcontent • Links to malware • Keyword response • Automated context free responses to keywords • Illegal Tweet Use • Nike gets red carded in the UK @stephendann
- 27. Spam • Trend hijacking • One or more #hashtags of trending events in a tweet unrelated to the trend • Mention • Replies using the @ command from accounts which do not follow the user, and which only post replies • Truthiness • Astroturfing message originating from an automated account @stephendann
- 28. Back to that note on your cards @stephendann
- 29. Conversational @stephendann Spam News Events @drstephendann @mktg3024 Status Pass Along @anzmac Phatic @stephendann
- 30. Conversational @stephendann Spam News Events @drstephendann @mktg3024 Status Pass Along @anzmac Phatic @stephendann
- 31. Conversational @stephendann Spam News Events @drstephendann @mktg3024 Status Pass Along @anzmac Phatic @stephendann
- 32. Implementing No battle plan survives contact with the enemy @stephendann
- 33. Kit out for Pass Along content • If this, then that • Buffer • Houtsuite • Crowdbooster • Instagram • Twylah • Wordpress (WP to Twitter) @stephendann
- 34. Measurement You may guess where some of this is going @stephendann
- 35. What type of data? Words or Numbers? Words help track the best performing content From Hubspot • Type • (pick a category box) • Format • text, image, video, file, link, tweet • Positioning • headline or an interesting line? • ask a question or state a fact? @stephendann
- 36. Defining the length of n+string Numbers Words • Klout • Storify Logarithmic scorecard • Captures the moments • Kred • Archive software Complicated score • TwapperKeeper* • Archivist • TwentyFeet • Twitter to PDF Performance Dashboard • Axel Bruns • Genius researcher @ QUT * Part of Hootsuite @stephendann
- 37. Results - @stephendann @stephendann
- 38. Conversational Category N % Exemplar Action 77 3% *waves at @USERNAME* Pass-along 66 2% @USERNAME Items under $1000 are exempt. http://is.gd/AV7K Query 480 17% Invading Germany from France. Who's with me? Response 850 30% @USERNAME Beware the polar bears. Word Words/ Dictionary Category N % >6 letters Linguistic Inquiry Results Count Sentence Words Action 77 3% 958 14.74 23.80 67.75 Conjunctions, Inhibition, Inclusive Biological processes Pass-along 66 2% 1020 18.89 21.86 54.31 OtherP, Period Query 480 17% 7032 10.13 21.22 75.33 Impersonal pronouns, Auxiliary verbs, Tentative, Discrepancy, QMark Response 850 30% 13637 17.05 21.97 73.84 3rd pers plural @stephendann
- 39. Conversational action 5% pass-along 4% query 33% response 58% @stephendann
- 41. Hashtags Used to associate a tweet with a topic • Self categorization technique Put the # symbol in front of a word or phrase #melbquake #priapdp #teambieber Came to Twitter as a user innovation based on use in other internet services <- Back @stephendann