Checking your bad mood at the office door

November 15th, 2009 by Daniele Quercia

(MSNBC)

Having a positive attitude, even striving for cheerful, in the workplace isn’t always easy. The ability to be positive is an essential leadership skill and responsibility.

  • Studies on “emotional contagions” in professional settings: you can catch a bad mood + expressing positive emotions and moods tends to enhance performance at individual, group and organizational levels
  • To put on a happy face, the first step is self awareness followed by self control (managing how you respond to others). Admit to yourself that, yes, you’re in bad mood, and then make sure you keep your crabbiness under wraps.

Defriending can bruise your ‘digital ego’

November 15th, 2009 by Daniele Quercia

CNN article

  • Researchers say our reaction to social rejection is the same whether it happens online or off
  • Elaine Fogel learned this after having a LinkedIn request be turned down
  • After experiencing online rejection, Kenneth Loflin altered the way he interacts online
  • Some users think you can avoid awkwardness of defriending by sending e-mail to explain

(plus from danah boyd (2006). Friends, Friendsters, and MySpace: ‘defriending’ someone by dropping them from a friend list can result – deliberately or accidentally – in upset feelings )

Who’s Viewed You? The Impact of Feedback in a mobile location Sharing System

November 9th, 2009 by Daniele Quercia

nice user study (CHI’09)

a mobile location sharing system. In our study, (n = 56), one group was given feedback in the form of a history of location requests, and a second group was given no feedback at all – feedback allays privacy concerns

ACM RecSys 2009 Keynote (in 140 character chunks)

October 23rd, 2009 by Neal Lathia

The third ACM RecSys conference started today in New York; unfortunately I could not make it. However, a number of people who I follow on Twitter are there (@xamat, @danielequercia, @barrysmyth)… and are tweeting away as the conference unfolds. You can follow the stream of #recsys09 tweets here. Although I’m sure that there are many details that do not make it into the 140 character-long tweets, they provide a real time snapshot of what is going on in the conference.

For example, the first keynote has just ended. Francisco Martin, Founder/CEO Strands, gave a talk about the “Top 10 Lessons Learned Developing, Deploying, and Operating Real-World Recommender Systems.” Here’s the twitter summary (note: copy/pasted and lightly edited to merge similar tweets).

Lesson 1 – Make sure a recommender is really needed! Do you have lots of recommendable items? Many diverse customers?… also think Return-on-Invesment… a more sophisticated recommender may not deliver a better ROI.

Lesson 2 – Make sure the recommendations make strategic sense. Is the best recommendation for the customer also the best for the business? What is the difference between a good and useful recommendation? Good recommendations vs useful recs; Obvious recommendations may not be useful; risky recs may deliver better long-term value

Lesson 3 - Choose the right partner! Select the right rec vendor vs hire some #recsys09 students. If you are a big company the best you can do is to organize a contest

Lesson 4 – Forget about cold-start problems (!) …. just be creative. The internet has the data you need (somewhere…)

Lesson 5 – Get the right balance between data and algorithms. 70% of the success of a #recsys is on the data, the other 30% on the algorithm

Lesson 6 – Finding correlated items is easy but deciding what, how, and when to present to the user is hard… or dont just recommend for the sake of it. Remember user attention is a scarce and valuable resource. Use it wisely! … dont make a recommendations to a customer who is just about to pay for items at the checkout! User interface should get at least 50% of your attention.

Lesson 7 – Dont’s waste time computing nearest neighbours (use social connections)… just mine the social graph. Might miss useful connections??

Lesson 8 – Dont wait to scale

Lesson 9 – Choose the right feedback mechanism. Stars vs thumbs …. the YouTube problem. More research on implicit and other feedback mechanisms is needed. The perfect rating system is no rating system! … focus on the interface. Seems to me this is one of the gaps in current research… algorithms > data > interface

Lesson 10 – Measure Everything! … business control and analytics is a big opportunity here.

Keynote Takeaway – Think about application context; Focus on interface as much as algs; Be creative with startup data. … the UI needs to get the lion’s share of the effort (50%) compared to algorithms (5%) , knowledge (20%), analytics (25%)

Code and other laws of urban space

October 23rd, 2009 by mike

Mobile phones offer more radical possibilities than ‘PC + internet’ in terms of bringing information into the real spatial environment, argues The City Project – which means architects and urban planners need to start engaging with the way space is experienced and manipulated through mobile software. Map-tagging and location-tracking could help planners to understand how space is used, reducing the tension between the ideal space of architecture and the real space of inhabitation.

So if the prophets of user-generated-everything need to learn that space matters, do those who dream of clean, Cartesian space also need to learn that use matters? No doubt – but to reduce location-aware software to a feedback channel from users to developers (in either sense), or to see it as another element in an architectural programme, would be to miss its truly radical potential, which would lie – if sufficiently open platforms could be developed – in enabling the unplanned, disorganised and ever-changing use of space, without architects.

The fallacy of web 2.0 utopians – motivational inforporn

October 17th, 2009 by Daniele Quercia

Chris Aderson said that the future of business is free. We are still waiting for this revolution (email Chris for a detailed revolutionary plan, he’ll be happy to answer).

Now comes Clay Shirky with the next revolution: “innovation can happen everywhere”, he said yesterday (1:39′ of his talk). OK, let’s buy few more copies of Shirky’s books and wait for the next Microsoft or Google coming from Tanzania. Meanwhile, let me tell you why I think speeches on web 2.0 revolutions are motivational infoporn.

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notes on Engaging Data

October 13th, 2009 by Daniele Quercia

The Engaging Data conference went very very well. Thanks to Caitlin and Francisca for their fantastic job! Few notes I’ve put quickly together:

Day 1

  • Peter Hirshberg gave a great keynote talk! He introduced interesting applications using real-time data: NYTE (use of phone calls from NY to cities around the world, City sense (tracking where people are right now), and City sourced (taking geocoded pictures and upload them directly to an official who can do something about it). Great quotes in his talk:
    • “with every augmentation comes amputations”. along those lines,  LBS turns us to starring at the screen instead of what’s around us.
    • ” Privacy is often eroded one convenience at a time” (by Chris Hughes of City Sourced)
  • A couple of researchers of SkyHook followed. They described how, by aggregating  data from GPS, cell phone towers, and wifi networks, they extract:
    • emergence bursts – lots of people come out at once
    • impedance clustering – accidents people want to get around
    • social affinity – large group of similar people

    Interestingly, they find spikes or dips with respect to a baseline level of actitivity (normal level of activity in a specific area)

  • Glen Urban of MIT Sloan introduced Ad Morphing. This system matches on line ads to individual cognitive style (e.g., deliberative/impulsive, analytical/holistic, verbal/visual). He concluded by introducing the recent migration of Ad Morphing on mobile phones (Concierge). The application would be to serve apps and ads that are useful on a phone’s screen.
  • Deborah Estrin of the Center for Embedded Networked Sensing introduced few projects:
  • Eric Paulos of CMU gave a beatiful talk that revolved around his research goals: improve science literacy, provide professional scientists with better data, develop new usage models for phones, enabling grass roots activism, & greater public understanding. From the same research group, Ian Li proposed powerful ways to improve self-awareness of physical activity.
  • Based on mobile phone calling data, Nathan Eagle is studying sex workers in Kenya (with Eduard Sanders), 150 undegrad smokers/recent quitters (with Yuelin Li), slums’ inhabitants (30% of people in slums carry mobile phones!) . He also touched on a spatial dynamic bayesian anomaly detection he developed with Eric Horvitz to answer questions including:
    • How do peoples’ movements and communications change when they get sick?
    • Calculate regional deviations from normal use and triangulate epicenter of disasters (e.g., tsunamis, earthquake)

    Great stuff!!!

  • Anmol Madan reported on his cool research on  how  things (e.g., political ideas, deseases) spread within face-to-face nets. He run an extensive study in one of the MIT dorms.
  • Michael Siegel of MIT Soan School mentioned that Japanese doctors created a system to capture EVERY piece of data in their hospital – every activity by every person (bar-code, RFID, EHR, test data). Check here & here.
  • Michiel Van Meeteren, Ate Poorthuis, and  Elenna Dugundji gave an engaging talk on mapping communities in large virtual social networks. They used twitter data to identify the indie mac community. They started from a central node and found the communities this node speaks to. The implications of this method are powerful – it may have jeopardize the protest during the recent Iranian elections. Very interesting work!!! Check the last abstract on this page.

Day 2

I was busy having meetings with my lab’s sponsors and followed just the panel session. Surprisinlgy, during the session, David Lazer pointed out that i’m the most central node in the twitter networks of the conference participants in  win (pic done using NodeXL) and engaging data (pic). wow!:-)

New Data

October 1st, 2009 by Daniele Quercia
  • 30 Resources to Find the Data You Need
  • New Reality Mining Data Available. From Nathan Eagle: “I am currently releasing the full Reality Mining dataset. It’s got loads of additional information – especially related to survey responses (friendships, recent illness, satisfaction, etc). The new ReadMe has a complete description. If you’d like access, just drop me an email. As I’m now involved in other projects, I haven’t had much time to look at this new data – so have at it. ”

giffgaff

September 24th, 2009 by Daniele Quercia

New mobile network to launch in the UK, built on and by its users. Radical new model? It’s called giffgaff. Youtube video.

New O2 service: ” customers will be encouraged to get directly involved in the business and be rewarded with various perks…. The service is a SIM-only service that gives customers cheaper calls if they refer friends and family, write blogs about it, and regularly post on its online forum. Customers who are actively involved will be given rebates twice a year and they will be given a few options on what to do with it: they will be able to use it for mobile calls and texts, take it as cash or even make a charitable donation.”

Netflix Prize – Round 2

September 21st, 2009 by Neal Lathia

The netflix prize winners have been announced, as well as the next $1 million competition. From here:

“The new challenge focuses on predicting the movie preferences of people who rarely or never rate the movies they rent. This will be deduced from more than 100 million data points, including information about renters’ ages, genders, ZIP codes, genre ratings and previously chosen movies.

Instead of a single $1 million prize, this new challenge will be split into one $500,000 award to the team judged to be leading after six months and an additional $500,000 to the team in the lead at the 18-month mark, when the contest is wrapped up.”

Interestingly, our previous discussion on the viability of the winner’s results has now an answer. From here:

The team’s 10 percent achievement will not be immediately incorporated into Netflix.com, said Neil Hunt, chief product officer.

“There are several hundred algorithms that contribute to he overall 10 percent improvement – all blended together,” Hunt said. “In order to make the computation feasible to generate the kinds of volumes of predictions that we needed for a real system – we’ve selected just a small number – two or three of those algorithms for direct implementation.”

Understanding the Spreading Patterns of Mobile Phone Viruses

August 10th, 2009 by Daniele Quercia

this science paper is very interesting. however, as pointed out here, it shows two major problems:

1) The paper more or less ignores the effects of technical safeguards built into modern smartphones operating systems.

2) the paper mentions that the reason why there hasn’t been more mobile outbreaks is that no smartphone operating system is dominating enough. Then in the next paragraph it mentions that Symbian has, oh, 65% market share of all smartphones.

Abstract

We model the mobility of mobile phone users to study the fundamental spreading patterns characterizing a mobile virus outbreak. We find that while Bluetooth viruses can reach all susceptible handsets with time, they spread slowly due to human mobility, offering ample opportunities to deploy antiviral software. In contrast, viruses utilizing multimedia messaging services could infect all users
in hours, but currently a phase transition on the underlying call graph limits them to only a small fraction of the susceptible users. These results explain the lack of a major mobile virus breakout so far and predict that once a mobile operating system´s market share reaches the phase transition point, viruses will pose a serious threat to mobile communications.

SIGIR ‘09

July 28th, 2009 by Daniele Quercia

Placing Flickr Photos on a Map. They place photos on a map based only on the tags of those photos. They exploit both info from nearby locations and spatial ambiguity

When More Is Less: The Paradox of Choice in Search Engine Use. They show that increasing recall works counter to user satisfaction, if it implies a choice from a more extensive set of result items. They call this phenomenon the paradox of choice. For example, having to choose from six results yielded both higher satisfaction and greater confidence than when there were 24 items to choose from

Telling Experts from Spammers: Expertise Ranking in Folksonomies. They presented a method in which power early-adopters  score highly. I call power early-adopters those who promptly tag items that happen to then become popular in the future.

Good Abandonment in Mobile and PC Internet Search. ” Investigation of when search abandonment is good (when the answer is right in the results list – no need to open page). Good abandonments are much more likely to occur on mobile device as opposed to PC; varies by locale (looked at US, Japan, China) and by category of query. “Our study has three key findings: First, queries potentially indicating good abandonment make up a significant portion of all abandoned queries. Second, the good abandonment rate from mobile search is significantly higher than that from PC search, across all locales tested. Third, classified by type of information need, the major classes of good abandonment vary dramatically by both locale and modality.”

Page Hunt: Improving Search Engines Using Human Computation Games. Microsoft Game Helps Make Search Better
Called Page Hunt, the game presents players with web pages and asks them to guess the queries that would produce the page within its first five results. Players score 100 points if the page is no.1 on the list, 90 points if it’s no.2, and so on. Bonuses are also awarded for avoiding frequently-used queries.

danah boyd’s gave a GREAT talk titled ‘The Searchable Nature of Acts in Networked Publics‘. In it, she debunked 3 myths about social networks:
1. There is only one type of social network. NO! There are 3 types of net
1) sociological network  (created from sociological study)
2) articulated network (created from listing friends)
3) behavioral network (created from interaction patterns)
those nets are very different but we have a tendency to assume they’re the same thing!!!

[Student Project Idea] Test whether the 3 types of social networks are related to each other and, if so, how!

2. Social ties are all equal. NO. The context of those ties and how strong they are are two important aspects, for example. (we have been discussing why context matters)
3. Content is King. In the tweet ‘i’m having for breakfast…’, the content isn’t important at all – it’s all about the awareness of sharing an experience.
danah then argued that social network sites are a type of networked public with four properties that are not typically present in face-to-face public life: persistence (what you say online it stays online), replicability (content can be duplicated (and can be taken of out-of-context – often u can’t replicate context)), searchability ( the potential visibility of content is great), and invisible audiences (we can only imagine the audience).  This networked public creates a new sense of what is public and what is private. For example, young people care deeply about their privacy, but their notion of privacy is very different from that of audults. finally,  danah introduced few stats on twitter (5% of accounts are protected, 22% include http://, 36% mention @user, 5% contain #hashtag, RT 3% are retweets, & spam accounts are proliferating) and highlighted some interesting research points for the future: 1)  how to make sense of content for such small bits of text; and 2) how social search can exploit analysis of the  network of twitters,  of context, and of tie strength.

IREVAL ‘09: Workshop on the Future of IR Evaluation

July 27th, 2009 by Neal Lathia

I recently attended the SIGIR ‘09 IREVAL workshop on the future of IR evaluation, where I presented a poster on evaluating collaborative filtering over time. The workshop began with invited talks from (IR-research superstars) Stephen Robertson, Susain Dumais, Chris Buckley (videolectures), and Georges Dupret, giving talks that drew on years of research experience. The workshop participants then broke into groups to discuss different proposals related to IR-evaluation, and the workshop closed with a group discussion about each proposal. As can be expected, this workshop brought up many more questions than it answered. Below I’ve transcribed some notes that I took during the day:

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Facebook Advertising With Your Pictures (+ How to Opt Out)

July 26th, 2009 by Neal Lathia

A recent post here discussed emerging technologies that can be used for advertising on the go- and the threat that they pose to individual privacy. It seems a similar case is now found in online social network sites; places where users volunteer personal information as they interact with their friends. As Daniele mentioned on twitter, a recent TechCrunch article reports on how Facebook now wants to move user information from the private to the public domain (in order to compete with Twitter?)

One of the small steps in doing so involves using your photos to advertise products to your friends:

Facebook occasionally pairs advertisements with relevant social actions from a user’s friends to create Facebook Ads. Facebook Ads make advertisements more interesting and more tailored to you and your friends. These respect all privacy rules. You may opt out of appearing in your friends’ Facebook Ads [..].

Interestingly, until I saw some facebook status updates like this one below, I had no idea:

ATTENTION! FACEBOOK has agreed to let 3rd party advertisers use YOUR posted pictures WITHOUT YOUR PERMISSION! To prevent this: Click on SETTINGS up at the top where you see the Log out link, select PRIVACY,then select NEWS FEEDS & WALL next select the tab that reads FACE BOOK ADS, there is a drop down box, select NO ONE. Then, SAVE your changes. ( RE-POST to let your friends know!)

I’m curious to see what kind of photos will appear, and if facebook measures any change in click-through rates with this feature. However, one of the points this seems to make is that a central aspect of privacy is not only giving users control over the flow of their information, but telling them where it may flow in the first place.

Recommender Systems @ SIGIR 2009

July 24th, 2009 by Neal Lathia

There were two sessions on recommender systems at this year’s ACM SIGIR (held in Boston). Overall, it was a good conference- organised well, run smoothly. It became very quickly apparent to me (a first-timer to SIGIR) that this is a tight community of researchers; there were many hugs at the opening drinks. Here is a quick summary of the recommender system papers and a couple other noteworthy papers/events.

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