Category Archives: sentiment analysis

Greek Election Tomorrow!

The Euro and the European currency union is the major topic of the second Greek parliamentary elections of this Spring, to be carried out tomorrow, on Sunday, June 17.

Ethersource has been reading Greek-language social media for the past few weeks. Our prediction:

  • ND will be leader in number of votes
  • one needs more than tallying frequency of mention or simple assessment of positive vs negative sentiment to use social media for predicting electoral outcomes

We at Gavagai have been following party politics in the Greek social media for the past few weeks and have found – as have the major political commentary sites – that the major players are the conservative ND and the socialist coalition Syriza. After gauging frequency of mention in Greek social media one would be likely to conclude that the election is safely in the hands of Syriza. See the graph below. Syriza gains much more attention in the Greek social media sphere than do other parties. (The dramatic spike in attention given to the fascist party XA has to do with one of their representatives demonstrating practical violence in a TV-debate, punching and slapping a political opponent on camera).

But that is not the entire story. Mentions alone do not translate to votes. A further analysis gives pause to the first prediction. The pie chart shows what proportion party mentions are coloured by mistrust and skepticism.

One cannot predict election results by counting mentions alone – the type of mention is important as well. We have previously cut up attitude in many ways, beyond what is done by most. Here we will look at distrust and doubt as an attitude. Skeptical, worried, and doubtful mentions indicate not propensity to vote but concern about the outcome. The tweets, blogs, and forum posts by Greek voters we read are not simply rooting for the author’s favourite party – they are analyses, each in its own way, of the election outcome. By aggregating the sentiment given in each of them we find a clearer picture than we would by simply counting and tabulating mentions.

Our analysis is as follows: Syriza and ND are most frequently mentioned. Syriza mentions carry a considerable amount of concern and mistrust. We assess this to mean that the electorate will gravitate towards ND rather than Syriza at the polling station: the likely leader in votes will be ND.

How ND will be able to put together a governable majority of representatives is another matter!

A Minute-by-minute Popularity Contest – Loreen versus Danny

Despite the fact that the Swedish part of the Eurovision Song Contest final was broadcast live, as a TV viewer it was impossible to get a sense of just how popular the artists were at a given point in time. Having access to Ethersource made sifting out meaningful blog posts and Tweets in real-time a breeze! Below are two graphs outlining, minute-by-minute, the popularity of the two top contestants as expressed in Swedish on-line social media for the day of the final (click the image for a larger version). Note that the popularity score of Loreen’s reaches higher during her performance than does Danny’s. In fact, looking at the scale and the contents of the two graphs, it is clear that the expressions of popularity towards Loreen is consequently higher throughout the day.

The popularity of Loreen and Danny Saucedo, measured minute-by-minute during the day of the final of the Swedish Eurovision Song Contest.

The popularity of Loreen and Danny Saucedo, measured minute-by-minute during the day of the final of the Swedish part of the Eurovision Song Contest. The annotations in red denotes the appearance on stage by the two artists.

The timing information for the performances of the artists is available at the official web site of the contest.

Fabulous Fest Forecast by Gavagai

Sweden’s contribution to the Eurovision Song Contest this year has been decided in yesterday’s finale with ten contestants. The winner of 2012 year’s Swedish music fest Melodifestivalen is Loreen, with the song “Euphoria”, which landed almost 700000 call-in votes from the at-home TV audience.

Using the Ethersource technology, Gavagai followed the on-line sentiment towards all contestants throughout the lead-up to the event. We are pleased to note that Gavagai’s forecast of the results based on expressions of appreciation in blog posts and tweets which was published in the paper edition of Svenska Dagbladet (SvD) in the morning prior to the event – was close enough to the actual outcome of the viewers’ votes to not only correctly predict the three top spots from the start field of ten contenders but to get their vote percentages pretty much right!

Talk comes cheap – demonstration counts!

This was fun! We will make similar public opinion forecasts in coming analyses, and return to the observations we can make from this event and these and similar data.

Artist Lars Vilks Attacked. Again.

At 6:45 pm, less than a minute after the news broke on Twitter, Ethersource picked up the first aversive signal relating to tonight’s attack on Lars Vilks. (We’ve covered him previously on this blog). This time, elements in the audience threw eggs at him during an evening lecture in Karlstad.

Of the major news outlets, the branch of Swedish Radio located in Karlstad was the quickest in publishing the news, putting it on their national web site at 7:43 pm (SR). The other players were roughly 30 to 45 minutes behind (DN, SVD, SVT). Having Ethersource doing real-time attitudinal analysis of the contents of Swedish Tweets would have brought the news to your attention even earlier.

Image 1: Aversive expressions related to Lars Vilks on February 21, 2012. The red circle shows the initial peak indicative of the egging event, targeting Vilks. The Tweet in Image 2 is the first one in the list of documents associated with the highlighted peak, easily accessible via the Ethersource GUI.

Image 2: The first Tweet picked up by Ethersource pertaining to egging event: "People in the audience just threw eggs at Lars Vilks and there was chaos"

 

 

Real-time Syndromic Surveillance of Social Media for Disease Symptoms related to Seasonal Influenza

  • We do real-time monitoring of  social media for disease symptoms
  • there is still no evidence of an outbreak of the seasonal flu in Sweden
  • we observe, however, an increasing trend in the intensity of symptoms

The inevitable influenza season will soon come knocking on our doors. How do we know when it has started, and how do we know just how severe it is? To this end, there are on-line tools for syndromic surveillance, aiding individual medical practitioners and national disease control centers alike to combat the spread of influenza. Internationally, perhaps the most well-known monitoring service is Google Flu Trends. Nationally, Influensakoll keeps track of the current state of flu-related illness in Sweden. Along the same lines, research carried out at the Swedish Institute for Infectious Disease Control (SMI) show the feasibility of using search queries submitted to the medical web site Vårdguiden for outbreak detection and monitoring. SMI also publishes weekly influenza reports based on input from labs and sentinels.

In addition, there is a growing effort in the research community of mining on-line social media, mostly Twitter, in English, and only by using keywords with the purpose of facilitating early-warning and outbreak detection to be used by health authorities in their planning and conducting targeted counter-measures to epidemic diseases.  Another interesting approach is that taken by the Iowa Electronic Health Market which is a prediction market for syndromic surveillance.

While the above mentioned services and research rely on either active participation on behalf of the users, or on keyword matching in social media feeds with the purpose of finding patterns, we’ve taken a different route to finding out the state of illness of Sweden. We’ve enhanced the barometer introduced earlier with concepts (not keywords) corresponding to a range of disease symptoms such as migraine, fever, expectorate, headache, nausea, sore throat, and head cold, facilitating the triangulation of more complex illnesses without having to wait for the bloggers, tweeters, forum participants, and facebookers out there to become so ill that they either actively seek answers related to their health condition, or start communicating using the actual name of the disease.

Our approach attempts to catch signs of illness early on, expressed as the participants in social media do what they usually do, that is, communicate with their peers. By focusing on the symptoms, we believe it is possible to get an early-warning of the seasonal flu, before anyone realizes it is what they are actually talking about. The image below illustrates the discrepancy between the score for the concept of influenza  (the green, nearly flat line at the bottom of the graph) and the scores for some of the symptoms of influenza; expectoration (blue line), headache (red line), and fever (yellow line). Clearly, people have not yet experienced the flu strongly enough to talk about it, although they talk loudly about some of its symptoms. Note that the graph reveals an increasing trend in the intensity of the symptoms! The Ethersource-based barometer thus serves as a complement to other surveillance tools in that it picks up on trends of (combinations of) symptoms earlier.

Expressions of the concepts expectoration, headache, fever, and influenza in Swedish social media, early December 2011. Note that while the influenza score is constantly low, the other three symptoms vary with the time-of-day, taking precedence over each other in various ways. Clearly, people have not yet experienced the flu strong enough to talk about it.

Expressions of the concepts expectoration, headache, fever, and influenza in Swedish social media, early December 2011. Note that while the influenza score is constantly low, the other three symptoms vary with the time-of-day, taking precedence over each other in various ways.

Gavagai’s Ethersource technology allows for the kind of syndromic surveillance of disease symptoms described in this blog post to be carried out in real-time, in any language.

Ethersource as a tool for data-driven journalism: the case of the fading interest in Julian Assange

The world has taken a keen interest in Wikileaks founder Julian Assange for quite some time now. A recent article in a leading Swedish newspaper, Svenska Dagbladet, claims that the general interest in Assange and Wikileaks has faded, an assertion based on frequency counts of search queries for Assange obtained from Google Trends.

By consulting Ethersource, we can confirm the trend at large. Now, there’s only so much to be said based on frequency counts of search queries. The fact is that people are still showing a clear interest in Assange. However valid the claim that the general public’s interest in Assange is fading might be, the odds for it are low, and as such it makes the story less interesting than it deserves to be.

Data-driven journalism can arguably dig deeper!

The Image below illustrates a different take on Assange. During October, we see two significant occasions on which people active in social media has expressed concerns not possible to distinguish by looking at frequency alone; they are benevolent, and they express worry (the blue and red curve, respectively). There may lurk an interesting story in any of these.

The benevolence expressed during October 13 to 19, is related to Assange’s engagement in the Occupy Wall Street movement. What might be more interesting is the fact that the benevolence falls, while at the same time, the worry rises sharply from November 1st and onward. The event underlying the changing characteristics of the graph at that time, is the extradition of Assange from the UK to Sweden where he is to be questioned over rape allegations. Surely, there must be a story to be told here, based on the views of the inhabitants of on-line social media.

Benevolence and worry expressed toward Julian Assange in English social media in October 2011.

Benevolence and worry expressed toward Julian Assange in English social media in October 2011.

Tracking Swedish political sympathies in social media

This Fall has been more eventful than many in Swedish politics, in spite of no real political events taking place. The recently elected leader of the Social Democratic Workers’ Party has been tangled into a mess of possibly excessive and in any case overcompensated housing allowance remuneration.

Our take:

  • Centerpartiet is fading out of view in spite of a newly elected and positively received leader.
  • The Social Democrats have become the focus for negative sentiment in the blogosphere, even to the point of distracting the established negative sentiment visavi Sverigedemokraterna.
  • A leadership change in the Social Democratic party is imminent.

Our charts of political sentiment over the period of September and October show how the Swedish political scene is expressed in text. The issue is published by Aftonbladet, a left-leaning Stockholm tabloid, on October 7, and the activity of text written on the Social Democrats explodes in intensity on that day. The timeline in Image 1 illustrates this, and the pie chart in Image 2 shows how different the attention towards the parties is to their polled approval ratings, with most notably Social Democrats and the xenophobic Sverigedemokraterna taking the stage to an extent out of proportion to their following. The bar chart in Image 3 shows how the frequency of mention in October (red bars) has changed (blue bars) compared to the previous month. (Also notable is how Centerpartiet is fading out of view in spite of electing a new leader on September 23, and that the yearly congress on October 14-16 for the liberal party Folkpartiet hardly made any impression in the frequency of mention.)

Image 1: Frequency of occurrences of Swedish political parties in Swedish social media

Image 1: Frequency of occurrences of Swedish political parties in Swedish social media during September and October 2011.

Image 2: The proportion of attention awarded the different political parties in Swedish social media in October 2011.

Image 2: The proportion of attention awarded the different political parties in Swedish social media in October 2011.

Image Z: The attention awarded to the political parties in October 2011 (red bars), along with the change from September (blue bars).

Image 3: The attention awarded to the political parties in October 2011 (red bars), along with the change from September (blue bars).

The bar chart in Image 4 shows how much violent and aversive sentiment is expressed visavi the various parties as a proportion of all written text in the month of October (red bars) and change from September (blue bars). This shows us how the constant pressure from the liberally oriented blogosphere in Sweden on the xenophobic Sverigedemokraterna to an unprecedented extent has been replaced with aversion towards the Social Democrats. The timeline in Image 5 shows how Social Demokrats are different from Sverigedemokraterna: the latter party is a violent fringe party and is frequently mentioned in bursts of violent rhetoric, often on their own initiative, generating peaks in the graph. The Social Democrats, by contrast, have now risen to a new higher and steady level of violent and aversive mention.

Image 4: Violent and aversive attitude expressed toward the political parties in October 2011 (red bars), along with the difference from September (blue bars)

Image 4: The violent attitudes expressed toward the political parties in October 2011 (red bars), along with the difference from September (blue bars)

Image 5: Violent attitudes expressed in Swedish social media toward the political parties over time.

Image 5: Violent and aversive attitude expressed in Swedish social media toward the political parties over time.

Image 6: The proportion of violent expressions in Swedish social media related to the political parties in October 2011.

Image 6: The proportion of violent and aversive expressions in Swedish social media related to the political parties in October 2011.

Finally, the time line in Image 7 shows how uncertainty as expressed in the Swedish social media has peaked with respect to the Social Democrats.

Image 7: Uncertainty related to the political parties expressed in Swedish social media during September and October 2011.

Image 7: Uncertainty related to the political parties expressed in Swedish social media during September and October 2011.

In conclusion, this analysis shows that the Social Democrats are in a different place than they were only a few weeks ago. The level of strongly negative rhetoric tinged by violence is on a steady level only matched by the habitually violent Sverigedemokraterna and the uncertain sentiment expressed in relation to the Social Democrats adds to a confusing image of the party. This pattern of mention and the now established scarring of the image of the party will be impossible to break without a considerable change in discourse. We cannot see how the current leader of the Social Democrats will be able to achieve this – our prediction is that he will not stay in office for long, and that after a grace period, the length of which is determined more by decency than political expediency, he and the current leadership will be very rapidly replaced.

Gavagai analyses the Greeks’ attitudes toward the cancelled referendum and the Eurozone

Greece has now officially scrapped plans for a referendum on the Euro bailout plan. Our research shows that a small majority (53%) of Greeks did not want the referendum, the exact subject matter and formulation of which remains unspecified and unclear. In our view, a majority (79%) of Greeks wants to remain in the eurozone. We note, however, that willingness to keep the Euro falls dramatically when the issue is raised in the context of austerity measures, which leads us to believe that if a referendum – on whether to remain in the Eurozone subject to harsh austerity conditions – was held today, almost every second Greek (46%) might opt for leaving the Eurozone. Similarly to patterns of violent demonstrations, the trend in pro-exit attitude is extremely volatile and directly linked to the current (daily) dominating topics, and to austerity and fear in particular. Between November 4th and 6th, there was a significant increase in pro-exit attitude, as illustrated by the image below.

This analysis is based on large volumes of Greek-language open sources including social media.

Pro-exit of the Eurozone as measured in Greek online media, November 4 to 6, 2011.

Greek pro-exit attitudes toward the Eurozone as measured in Greek online media, November 4 to 6, 2011.

Greece: Politics, Economics, and Rowdy Behaviour separated

Many of us are trying to keep track of what is going on in Greece these days. We will have reason to give you more news flashes of how events in Greece are being narrated and reported – here is a first peek at results from our ongoing monitor. This monitor is based on English-language reports, chatter, tweets, blog and forum posts on the Greek crisis.

Greece in news and social media in October 2011

Graph of mentions of Greece in news and social media in October 2011

Noticeable is that there is a clear spike in our vpi signal in mid-October (blue ring). This signal – the violence propensity index – indicates violent sentiment. The news reports we have collected from those days do not belie this. Negativity in general gives no spike here – these texts report on violence but do so dispassionately. By contrast, the last two days, in wake of rising concern over the impending referendum and political uncertainty in Greece, we find a rising trend (red ring) of negative signal, both editorial reporting and comments – but no violence.

This, of course, is vastly preferable! (And from our point of view it is pleasing to be able to separate political and economic browbeating, however heated, from tear gas and brick throwing.)