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Customer communication in twitter

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  • 1. Customer Communication in Twitter
    A casestudyof Toyota in a crisis
    Stefan Stieglitz
    Nina Krüger
    Linh Dang-Xuan
    DIATA ´11
  • 2. Agenda
    Motivation and Background
    Related Work
    Research Design
    Summary
    Research Approach for the further study
    1
    Customer Communication in Twitter
  • 3. Change in Public Communication
    2
    Customer Communication in Twitter
    Media (journalists as gatekeepers)
    Agenda Setting
    Organization
    (enterprise, political player, …)
    Public one-way communication
    Media Monitoring
    Customers, Citizens
    Public Relations
    Public Feedback, Questions, opinions, customer innovation
    Social Mediamarketing
    Ideas, Innovations, opinions, Trends, complains, recommendations, etc…
    Communication between social media users
    • Complains
    • 4. Trends etc.
    Viral marketing, undercover actions
    Social Media
  • 5. What’s the difference?
    Opinion leaders are hard to identify
    Much more data and richer information
    Possibility to track data automatically and analyze them (digital information, ...) very fast (e.g. direct feedback on campaigns)
    Everybody has a voice – risks and chances for companies
    Long tail – opinion gathering
    Choice of words – no strict rules like in press releases, different styles because of different platforms
    3
    Customer Communication in Twitter
  • 6. Research Questions
    Goals: getting a deeper understanding about the dynamics of the structures of communication, the participation of the stakeholder and their sentiments in the communication.
    Are crisis-related issues in twitter discussed (like in the classic media) and are these discussions characterized by peaks and buzzing-stages? Do involved user post higher frequented in peaks than in buzzing stages?
    Are the postings in the peaks filled with more sentiment-words than in the buzzing stages?
    Is there a difference between sentiments in Tweets created by power-tweeters (PT) only and the sentiments in Tweets created by all participants of the sample?
    4
    Customer Communication in Twitter
  • 7. Agenda
    Motivation and Background
    Related Work
    Research Design
    Summary
    Research Approach for the further study
    5
    Customer Communication in Twitter
  • 8. Sentiment in Twitter Messages
    Sentiment Analysis
    Sentiment analysis of Tweets: Events in the social, political, cultural and economic sphere do have a significant, immediate and highly specific effect on the various dimensions of public mood (Bollen et al., 2009).
    Link measures of public opinion derived from polls to sentiment measured from Twitter messages: Sentiment word frequencies in contemporaneous Twitter messages do correlate with several public opinion time series such as surveys on consumer confidence and political opinion over the 2008 to 2009 period (O’Connor et al., 2010).
    Study of political tweets around the 2009 German federal election: Tweet sentiment (e.g., positive and negative emotions associated with a politician) corresponds closely to voters’ political preferences(Tumasjanet al., 2010).
    6
    Customer Communication in Twitter
  • 9. Agenda
    Motivation and Background
    Related Work
    Research Design
    Summary
    Research Approach for the further study
    7
    Customer Communication in Twitter
  • 10. Proceeding
    Objects ofstudy: the Top10 players in theautomotiveindustry
    Identification of appropriate keywords using classic print media:
    Identification of keywords by scanning the New York Times over a periode of two weeks, analyzing these articles which are related to one of the carmakers.
    Structural analysis of the course topics:
    Observation, analysis and documentation of public communication inTwitter using the keywords found with the help of a software prototype
    Cleaningupthedata
    8
    Customer Communication in Twitter
  • 11. Case selection
    Identificationof an issue
    The large-scalecarrecall due to a technical fault in the gas pedals and thebreaks
    Usingthekeyword-combination „recall/-s“, „Toyota“
    Implementation ofthe Issue Scanning fortheperiode 13-31 calendarweek:
    732.003 Tweets: „Toyota“
    37.232 Tweets: „recall“ und „Toyota“
    9
    Customer Communication in Twitter
  • 12. Outline data
    5.870 Tweets withHashtags (1.896 #toyota, 851 #recall) (16%)
    • 3.190 Tweets withlinked URLs (8,6%)
    Relatively uniform distribution of users involved in the communication
    The 10 mostactive Twitter accountsdid 6.237 postings all in all (17,5 % of all Tweets)
    Most activeaccount: 1.237 Tweets (Toyota_recall)
    The twoidentifiedofficial Toyota-accountpublishedonly 237 and 164 Tweets
    10
    Customer Communication in Twitter
  • 13. Findings
    11
    Customer Communication in Twitter
  • 14. Sentiment Analysis
    Classifyingthepolarityof a giventextatthedocument, sentence, orfeature/aspectlevel
    Linguisticdimensions
    Positive emotions (positive feelings, optimism)
    Negative emotions (anger, anxiety, sadness)
    Example: Creatingsentimentprofileforcompanies, partiesoraffiliatedindividuals (e.g., in the form of positive/negative-emotion scales)
    12
    Customer Communication in Twitter
  • 15. Findings
    13
    Customer Communication in Twitter
    Uniform percentage of sentiment words in the discussion
    A clear tendency of a stronger polarization in peaks
  • 16. 14
    Customer Communication in Twitter
    Findings
    Isthere a differencebetweensentiments in Tweets createdby power-tweeters (PT) only and thesentiments in Tweets createdby all participantsofthesample?
  • 17. Agenda
    Motivation and Background
    Research Approaches
    Related Work
    Summary
    Research Approach for the further study
    15
    Customer Communication in Twitter
  • 18. Summary
    Organization-relatedissuesarediscussed in Twitter
    Usingtheissuescanningkeywordscanidentifytopicsfortrackingdynamics
    In crisis situations, more individuals participate in the discussion (the contribution per user does not rise)
    In peak periods, there are clear trends in the discussion to positive or negative sentiments
    Measures may differ in different types of discussion
    16
    Customer Communication in Twitter
  • 19. Agenda
    Motivation and Background
    Related Work
    Research Design
    Summary
    Research Approaches for the further study
    17
    Customer Communication in Twitter
  • 20. Further Research
    18
    • Research on dynamics of specific topics in social networks
    • 21. Comparative studies of different cases
    • 22. Content analysis of the Tweets
    • 23. Social Network analysis
    Customer Communication in Twitter
  • 24. Many thanks for your attention!
    19
    Customer Communication in Twitter
  • 25. 28.09.2011
    20
    Nina Krüger M.A.
    nina.krueger@wi.uni-muenster.de
    0251- 83 38 014

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