Amy Guy

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Showing posts with label social media. Show all posts
Showing posts with label social media. Show all posts

Thursday, July 11, 2013

#SSSW2013: Social semantics and serendipity

We started work on the serendipity project before breakfast today, although I didn't make it down as early as some of my teammates.

To start the day, Fabio Ciravenga talked about some really exciting practical applications of monitoring and analysing social media streams.  It's particularly interesting during emergencies, or large events where problems might occur.  The people on the ground make the perfect sensors if you can work out the differences between people who are saying something useful and who aren't; people who are really there, and people who are speculating or asking about the situation.  A main problem has been that people tweet crap.  They were trying to monitor a house fire, but so many people were tweeting lyrics from Adele's various singles at the time, which all apparently contain references to fire, it was almost impossible.

They also put (or tapped into existing) sensors in peoples' cars to monitor driving patterns with the aim of more fairly charging for car insurance.  I told my Mum about this the other day, and she was pretty alarmed by the idea.  Which made me wonder how they'll get mass adoption, if it's going to go anywhere.

Fabio did have some interesting things to say about using all this data ethically though, and never working for someone who is going to take that away from you.  But in case the 'bad guys' do find out about all this data you have about people, keep a magnet handy.

My notes are here.

This was followed by a hands-on session where we got to mess with a mini version of the twitter topic monitoring system that Fabio's team use at large events, to try to answer questions about the Tour de France only by manipulating the incoming social media streams and following only links which came through that.

Spanish omelette sandwiches were an amazing outdoor leisurely lunch.  We headed to the pool down the road and chilled out there for a couple of hours.  Us tough British folk found the water pleasantly tepid, whilst all those wimpy Europeans and Latin Americans shivered on the grass.  They'd made such a fuss in advance about how cold the pool was going to be.

We regrouped that afternoon to work on Project Cusack, creating a slide deck of pictures from Serendipity.  I don't like slides with too much to read on, so I enforced this.  The imagery from the movie will be lost on most people, but we have at least managed to choose pictures of John Cusack with appropriate expressions for each part of the presentation.  We worked outside in the forest, because Oscar's 3G was faster than the residence wifi.



We also brainstormed for the required short film, which we only just discovered doesn't have to be about our project.

We returned to the residence to find everyone eating ham and cheese, and attempted to get some shots for our film, but other people were unwilling to participate.

That evening we ate tasty vegetable soup, weird (in a bad way) pasta in a creamy onion sauce, and chocolatey ice cream cake.  The tutors spontaneously organised a game where students had to arrange the tutors by age, which was funny.  Someone suggested the tutors ought to play it with the students.  Obviously there were too many students, but they elected to find the youngest student, and that turned out to be me.

Wednesday, July 10, 2013

#SSSW2013: Practical semantics and human nature

Harith Alani talked about using semantics to solve problems around evaluating the success of social media use in business.  The SIOC ontology is widely used to describe online community information.  It's not as simple as measuring someone's engagement with a brand's online presence - people are 'likeaholics' on Facebook, so you have to look at someone's whole behaviour profile to judge whether their like means anything or not.  It's no good just aggregating your data and spewing out numbers - you have to browse the data and try to understand where it came from.

He mentioned how little work has been done in classifying community types.  Most of the work that has been done seems to be with social networks internal to an organisation.  A bottom-up approach to community analysis can handle emergent behaviours and cope with role changes over time.  Looking at behaviour categories and roles can help an organisation to decide who to concentrate on supporting and how in order to sustain the community.  The results they have seen so far suggest that a stable mix of the different types of behaviours are needed to increase activities in forums - but they don't know what causes what.  They're reaching a point where they can use their behaviour analysis to guess what's going to happen to a community: how long it will last, how fast it will grow, how many replies a certain type of post is likely to get, etc.

Next they want to be able to classify community types, and be able to look at activities within a community over a period of time and automatically discover what kind of community it is; it might be something different than what it was set up for.

They created an alternative Maslow's Hierarchy of Needs to correspond with activities seen on forums, and found that most people are happy to stay at the lower levels of the hierarchy.  For example, join a community, lurk for a bit, ask one question and leave.  Not everyone wants or needs to be a power user.

Papers are being written that find patterns in individual datasets for a particular community in a particular context.  Harith and his team are getting tired of this; they want to generalise across communities.  So they took seven datasets and looked at how the analysis features differed as well as comparing the results across community types, randomness (vs. topicality) of datasets, and compared similar experiments.

Upcoming work includes the Reel Lives project, in which UoE is involved.  They're taking media fragments - photos, videos, audio clips, text recorded as audio - and creating automated compilations to tell a story.

Another is social methods to change energy consumption behaviour.  LiSC in Lincoln did something in this area back in the day.. an app that posted that you were listening to an embarrassing song on your facebook feed if you left your lights on.

Notes from Harith's talk are here.



From Tommaso Di Noia's talk, I learnt that recommender systems have a lot of maths behind them, especially for evaluating things, and reinforced something I already knew: I don't maths good enough to be taken seriously by most of the Informatics world.  I think I understand the principles behind the maths, but when something is descried in just maths, I have no idea what it relates to.  I'll work on this.

Real world recommender systems use a variety of approaches, including collaborative (based on similar users' profiles); knowledge-based (domain knowledge, no user history); item-based (similarities between items); content-based (combination of item descriptions and profile of user interests).  Linked Open Data is used to mitigate a lack of information about entities, and helps with recommending across multiple domains.  You do have to filter the LD you use before feeding it to your recommender system though, to avoid noise.  Notes here.

Tommaso's talk was followed up by a hands-on session, where we got to poke about with some of the tools he mentioned, including FRED (transforms natural language to RDF/OWL); Tipalo (gets entity types from natural language text); and using DBpedia to feed a recommender system.

Then we worked on our mini-projects for the afternoon.  We made some progress towards breaking down the concept of serendipity and working out what properties we might need to represent as linked data, and how we could observer a user and work out if/when/how they were having serendipitous experiences without intruding too much.

In the evening we took a coach to 'nearby' historical town Segovia.  Apparently an extremely motion-sickness-inducing two and a half hour coach journey around twisty mountain paths is 'nearby'.  Fortunately I was distracted from this horrible journey by a conversation with Lynda Hardman, which I wish I had recorded.  Lynda challenged various aspects of my PhD until I could explain/justify them reasonably, including:

  • Why digital creatives? (I'm used to that one now).
  • What is the outcome?
  • Why Semantic Web for this?

She also recommended a number of resources, including theses of her recent former students to help me with a structure for my own, and advice on maintaining a healthy balance between thinking and doing.

Plus she used to live in Edinburgh, more or less across the road from where I live now.  Cool.  Thanks Lynda!  You haven't heard the last of me :)

#travel

Once we got to Segovia, we had a guided tour of the ancient Roman architecture, interesting building façades and local legends.  It was a very good tour, but too hot to really focus.  Then they took us to a restaurant for a local speciality.  I was all set to write a whole individual blog post surveying the barbaric nature of human beings, but I didn't do it straight away and now the passion has faded slightly, so I'll leave it at a paragraph.  Some people watched the local 'ceremony' out of morbid curiosity I imagine, but it was the fact that so many people took so much pleasure in the idea of violently hacking up bodies of three-week-old piglets that really bothered me.  Fortunately the surging standing crowd allowed me (and only one other) to inconspicuously sit it out.  The veggie option was tasty, but it was difficult to really enjoy the rest of the evening whilst wondering vaguely about the states of minds of most of the people I was sharing a table with.

[Notes] Harith Alani at #SSSW2013

Social Media Analytics with a Pinch of Semantics

Using semantics to solve problems (not solving problems of semantics).

SM for businesses:

  • Analytics.
  • How to measure success?

SM silos impeding progress.
In-house social platforms increasing, so even more so.

SIOC to integrate online community information.
SIOC + FOAF + SKOS.

FB Graph.
People are likeaholics.  Their 'likes' become meaningless, so you need to take this into account when making recommendations.
Browse your data and understand user actions.

Behaviour analysis.

Bottom-up analysis.
Can handle unexpected or emerging behaviours.

  • Community members classified into roles.
  • Identify unknown roles.
  • Cope with role changes over time.
  • Clustering to identify emerging roles.

eg. focussed novice; mixed novice; distributed expert; ...
Spectrum across users you can or can't do without.

Extending an ontology built on SIOC.

Encoding rules in ontologies with SPIN.

Three categories of features:

  • Social features (people you follow, people follow you, ...)
  • Content features (what you're posting, keywords, ...)
  • Topical/semantic features

Which behaviour categories you need to cater for more than others?  How roles impact activity in online community.

Consistently see that you need some sort of stable mixture of behaviours for activities in forums to increase.

==> Don't know what's causing which.

What is a healthy community?

Use behaviour analysis to guess what's going to happen to community. Eg.

  • Churn rate.
  • User count.
  • Seeds/non-seeds prop (how many / if people reply to you).
  • Clustering.

Unexpected: the fewer focused experts in the community, the more posts received a reply.
(But quality of answers?)

Community types (Little work in this space)

Muller, M. (CHI 2012) community types in IBM Connections:

  • Communities of Practice
  • Teams
  • Technical support
  • ..
  • .. (see slides..)

Need an ontology and inference engine of community types.
Wants an automated process to tell you what type of community it is - it might be something it wasn't set up for.
Then you could determine what sort of patterns you would expect to find.
Noone has done this yet.

Measurements of value and satisfaction

Answers different across communities.  They ran it on IBM Connections - corporate community.

Most of this work is for managers of communities - see what's happening and help to predict what might be coming next.

Can classify users based on Maslow's Hierarchy of Needs?
Mapping the hierarchy to social media communities.
~90% users happily staying at the lower levels of the 'needs hierarchy'.

Behaviour evolution patterns

What paths they follow over time.
eg. people who become moderators eventually.

Engagement analysis

What's the best way to write a tweet so that people care about it?
Which posts are likely to generate more attention?

Getting bored of people finding patterns in individual datasets.  What can be generalised to other communities?

So experimented with 7 datasets and looked at how results differed across:

  • community types.
  • randomness (vs. topicality) of datasets.
  • related experiments.

And people use different features.

Semantic sentiment analysis in social media

Too much research going on, especially on twitter.

Extract semantic concepts from tweets; likely sentiment for a concept.
Tweetnator.
Semantics increases accuracy by 6.5% for negative sentiment; 4.8% for positive sentiment.

OUSocial.
Students don't use in-house networks because they already use facebook groups etc. Want to analyse what's happening on them.

Upcoming

Reel Lives (inc. Ed.)
Fragmented digital selves.
Want to automate compilations of media (photos, messages) posted online.

Changing energy consumption behaviour.
Providing information is not enough.

Social Eco feedback technology.

Sunday, March 03, 2013

Notes on SW and Communities

Lawrence, K.F., schraefel, m.c.: Bringing communities to the semantic web and the semantic
web to communities. In: Proceedings of WWW2006. (2006)



Research into SW communities:

  • Communities of practice
  • Social networks, eg. FOAF

Compare with other definitions of communities outside of SW.
Concept: Internet Based Community Network, has properties of COP and SN.
Case study: Amateur Fiction Online.

Early community definitions, Howard Rheingold: "..webs of personal relationships in cyberspace."

1996 CSCW Conference defined prototypical attributes of communities (Whittacker):

  • Shared goal / interest / need
  • Repeated active participation, emotional ties and shared activities.
  • Shared resources and access policies
  • Information, support and services reciprocated between members ( overlap with ^ ?)
  • Shared context (culture, language)
  • Can be applied to virtual and offline communities.

-> More attributes = clearer example of community.

Preece:

  • Social interaction
  • Shared purpose
  • Common set of expected behaviours
  • Computer system that facilitates and mediates communication


^^ Things in common.  Whittacker's is more inclusive/broad.

So for a SW SN:

  • Accessible via browser
  • Explicit links between users
  • System supports creation of these links
  • Links are visible and browseable

COP or SN may describe a community, not necessarily.  IBCN will do, and could be a COP or SN too.

Problem of Amateur Fic. is fluctuation of archive.  Personal sites go down etc.  How to find a story you remember a bit of?

IBCN is also combination of WBSN and virtual community.
Lack of incentive to use FOAF (eg. on LiveJournal etc) (Plus ignorance).
Doesn't offer anything they don't already have.
They don't use much metadata, just tons of human-readable stuff.

SW would allow:

  • "better integration of distributed systems"
  • "improved searching and filtering"
  • "more personalised services"
    •   experienced users
      • expand options
      •   new ways to interact
    •  new users
      •   ease introduction re: unwritten rules, expectations, terminologies


FOP extension to FOAF for anonymous identities.
('Fan Online Persona' - why not just 'Online Persona'?)
Consistency likely in community-based system because of advantages of reputation etc.  Identity cost.
Shared set of behaviour values, or risk losing rep.
Reputation gained by taking part.  (definitive part of community).
Additionally by creating works.

foaf:document and foaf:groups allow users to give details about their own creations and review work of others.

OntoMedia to describe content complements FOP.
Options in FOP gathered from study of metadata of works in mailing lists, websites and groups.
Recommender system -> notification system.

Allow SNS of writers to be studied at friend level and collaboration level.

Application to allow users to create FOP under development...