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Le nuove tecnologie di Social Networking e le Imprese - Giuseppe Manco

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  • 1. Le  nuove  tecnologie  di  Social   Networking  e  le  imprese   Giuseppe  Manco   ICAR-­‐CNR   manco@icar.cnr.it    
  • 2. Giuseppe  Manco  •  Ricercatore  presso  ICAR-­‐CNR  •  Aree  di  interesse   –  Data  Analysis,  Social  Networks,  sistemi  di  recommendaCon  
  • 3. CONNETTERSI,  COMUNICARE  
  • 4. Sei  gradi  di  separazione  
  • 5. Myspace:  110  milioni  di  uten?  
  • 6. Cos’è  una  rete  sociale?  Traditional Media Broadcast Media: One-to-Many One to Many Communication Media: One-to-One
  • 7. Characteristics na  Socialsociale?   Cos’è  u of rete   MediaEveryone can be a media outlet•  User  generated  content  Disappearing of communications barrier•  Rich Usernriched  content   User  e Interaction User-Generated Contents User  interacCon  •  User Enriched Contents•  User developed widgetsubiqua   Comunicazione   Collaborative environment•  Collective Wisdom environment   CollaboraCve   C Long Tail•  …   Broadcast Media Social MediaFilter, then Publish Publish, then Filter
  • 8. User  generated  content  
  • 9. User  interac?on  
  • 10. Comunicazione   ubiqua  
  • 11. AEvità  condivise  
  • 12. I  websites  più  visitaC  •  Il  traffico  internet  più  alto  (daC  Alexa,  oQobre   2012)   1   Facebook   11   Blogspot   2   Google   12   LinkedIn   3   YouTube   13   Taobao   4   Yahoo   14   Google  India   5     Baidoo   15   Yahoo  Japan   6   wikipedia   16   Sina.com.cn   7   Windows  live   17   msn   8   TwiQer   18   Google  hk   9   QQ.com   19   Google  de   10   Amazon   20   Bing  
  • 13. Il  ruolo  fondamentale  dei  social  media  
  • 14. TIPOLOGIE  DI  RETE  
  • 15. L’Universo  Social  Media   Social   Networking   Content   Social   Blogs   Media   sharing   Wki   Forum  
  • 16. QUALI  OPPORTUNITÀ?  
  • 17. L’azienda  e  i  social  networks  •  Pubbliche  relazioni  •  Customer  Support  •  Market  Research  •  Brand  MarkeCng  •  PromoCons  •  Consumer  EducaCon  •  Sales  •  New  Product  Development  •  Customer  RelaConship   Management  
  • 18. SOCIAL  MEDIA  ANALYTICS  
  • 19. DaC,  daC,  daC  •  Grossi  volumi,  grande  varietà   –  Milioni  di  utenC,  milioni  di  contenuC   –  testuale,  MulCmediale  (immagini,   video,  etc.)     –  Milioni  di  connessioni   –  Tendenze,  preferenze,   comportamenC,  …  •  I  daC  sono  open  e  facili  da  accedere   –  Facili  da  reperire   –  Di  pubblico  dominio   –   Developers  APIs   –   Spidering  the  Web  
  • 20. Le  opportunità   Any user can share and contribute content, tente  può  condividere  e   •  Ogni  u express opinions, link to others contribuire  ai  contenuC,   This means: Can data-mine opinions esprimere  opinioni,  collegarsi  ad   and behaviors of millions of users to altri   gain insights into: •  Questo  significa:   Human behavior –  Human  behavior   Marketing analytics –  MarkeCng  analyCcs     Product sentiment –  Product  senCment  8/21/2011 Jure Leskovec:Social Media Analytics (KDD 11 tutorial) 6
  • 21. Actionable IntelligenceConsumer Generated,Not Edited,Not Authenticated 8/21/2011 Jure Leskovec:Social Media Analytics (KDD 11 tutorial) 7
  • 22. Applicazioni:  ReputaCon  management  •  Consumer  Brand  AnalyCcs   –  Cosa  dice  la  gente  sul  mio  marchio?    •  MarkeCng  CommunicaCons   –  Determinare  se  le  campagne  che   pianifico  saranno  efficaci  •  Product  reviews   –  Estrazione  automaCca  di  review  e   informazioni  su  prodom  e  servizi   •  Facile  da  usare,  confortevole,  prezzo   adeguato,  …    
  • 23. Applicazioni:  Responsività  •  CiCzen  response    •  feedbacks  su  temaCche  poliCche  •  Campagne  poliCche –  Perché  la  gente  supporta  un   candidato?    •  Law  enforcement   –  MovimenC  dissidenC  su  TwiQer     –  Minority  report    hQp://www.nyCmes.com/2011/08/16/us/16police.html?_r=1    
  • 24. Applicazioni:  Viral  MarkeCng  •  Viral  markeCng:     –  Raccomandazioni  personlizzate  •   Il  ruolo  dei  forum  online:   –  79.2%  dei  partecipanC  ai  forum  aiutano   gli  utenC  connessi  a  prendere  decisioni   relaCve  a  un  prodoQo   –  65%  dei  partecipanC  ai  forum   condividono  consigli  (offline  o   personalizzaC)  basaC  sulle  informazioni   che  hanno  leQo  online        hQp://www.socialmediaexaminer.com/new-­‐studies-­‐show-­‐value-­‐of-­‐social-­‐me  
  • 25. Applicazioni:  Human  Behavior  analysis   Process social media content, provide tools • for analysts to:ontenuC,  e  usufruire  di  tools  per     Processare  I  c –  IdenCficare  rnetworks: groups, members Identify social eC  sociali:  gruppi,  membri   –  IdenCficare  tand sentiment Identify topics opics  e  senCments   Predictive Modeling Link Diagrams Social Media Content8/21/2011 Jure Leskovec:Social Media Analytics (KDD 11 tutorial) 12
  • 26. Relevance,  Authority,  SenCment  Page 27 •  Le  tre  dimensioni  dell’interazione  sociale  ilities to pro-ogs.and markets are a very dia because Figure 1: Relevance, authority and sentiment at the blog level. ly inaccessi- IBM’s  topic-­‐based  blog  evaluator     c customer insights and opin- Finding the Relevant Blogsan address several interesting OUR FIRST OBJECTIVE is to filter the vast blogosphere
  • 27. SenCment  DetecCon  •  E’  possibile  caraQerizzare  (in  maniera   automaCca)  il  tono  di  una  discussione?   ORMS3701_FTRs 2/3/10 4:56 PM Page 28 M A R K E T I N G & S O C I A L M E D I A belief of the sentiment IBM  Social  Media  AnalyCcs   associated with it. It is pos- sible to learn from such labeled words in conjunc- tion with labeled docu- ments. Furthermore, the selection of words and doc- uments to be labeled can be made algorithmically. Such an approach is known as active dual super- vision [5], and it can greatly reduce the effort required to label examples in a new domain. Even though there are expressions of sentiment that are domain-specific, Figure 2: Identifying and addressing negative sentiment. there is still a large amount of overlap in how positive and
  • 28. Misurare  Influence  e  Authority  •  Chi  sono  gli  utenC  suscembili?    •  Come  si  propaga  un’informazione?  •  Quando  un’opinione  è  affidabile?  
  • 29. Emerging  Topics  •  Higher-­‐level  concepts  dall’informazione  che  si  distribuisce  •  Come  variano  quesC  concem?   hQp://memetracker.org   Most  menConed  phrases  in  the  US  presidenCal  campaign  
  • 30. I  social  media  e  le  imprese…  •  Due  prospemve   –  Nuovi  scenari  e  modelli  di  interazione   –  AnalyCcs  •  StreQa  cooperazione  con  ricerca  e   innovazione   –  Nuovi  challenges   –  Opportunità  enormi