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Posts Tagged ‘sentiment’

Tracking the Mood About Gas Prices on Twitter: A Case Study

by January 25, 2012

As another test of our strategy for teasing out public opinion from social media, we explored measuring mood about gas prices on Twitter. This post summarizes the findings from this case study. Incidentally, we are set up to measure mood from Twitter on an ongoing basis, although we would need to find a partner to help defray the ongoing costs of crowdsourcing the sentiment judgments. (See this post to read more about our decision to examine the discussion about gas prices on Twitter.)

The sentiment we mapped was culled from tweets gathered from four weeks’ worth of data starting on May 22nd, 2011. This time period was chosen to coincide with Memorial Day, a holiday during which many Americans travel by car. Our team was curious to see whether there would be an uptick in either the volume of tweets about gas prices during this period or a noticeable change in sentiment about these prices. (more…)

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Sentiment Analysis Milestone: More Than One Million Human Judgments

by June 27, 2011

judgment-shot We have developed a process, dubbed Pulse, to extract nuanced sentiment from social media, like Twitter. We recognized early on that tools weren’t available to adequately answer specific questions, such as: “What’s the mood about today’s weather?” or “What portion of Twitter authors who discuss global warming believe that it is occurring?” or “Did Apple or Google have a more favorable buzz during this year’s South-by-Southwest Interactive?” Specifically, we concluded that it was necessary to get humans involved in the process—especially for Twitter posts, or tweets, which are often cryptic and have meaning that might be missed by a computer algorithm.

So, we turned to crowdsourcing.

However, successfully leveraging the power of the crowd for our sentiment analyses required cultivating the crowd, which we have achieved by working with partner CrowdFlower. In short, CrowdFlower offers an approach where we can access various work channels (we have relied mostly on Amazon’s Mechanical Turk), yet do so by layering on a quality control filter. Specifically, we intersperse within jobs what CrowdFlower terms “gold” units—in our case, tweets for which we already know the sentiment.  Workers build trustworthiness scores by getting the gold units correct. If they miss a gold unit, they get some feedback from us that has been tailored to that unit, such as “This person is happy that their garden is getting rain, so this should be marked as a positive emotion about the weather.”

We have been running a lot of jobs through CrowdFlower, but only recently did I step back and add up the tweets processed. For more than 200,000 individual tweets, we have received more than 1,000,000 trusted, human judgments from the CrowdFlower workforce! I know our research team, who had to do a bunch of judgments early on as we worked out a viable strategy, are grateful that we could get help from the crowd.

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Teasing Out Opinions About Global Warming From Twitter

by June 24, 2011

snapshot-ca A couple of months ago, we posted results from a quick sampling of mood about global warming in the Twittersphere that was featured in Momentum, the publication of the University of Minnesota’s Institute on the Environment. Along with our work on weather mood and mood about gas prices, we are on the verge of releasing a more in-depth analysis of sentiment about global warming. Here, we explain the method behind our sentiment analysis related to global warming, building off an earlier post that presented some of the details of our methodology on studying global warming chatter. (more…)

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Relevancy and Context are “Critical” with Sentiment Analysis

by May 24, 2011

September 11 Whenever I come across a piece that highlights how tricky sentiment analysis truly is, I tend to be encouraged more often than dissuaded to keep trying to figure it out.

Sentiment analysis is tough—not as in strict, like a teacher is tough, or in resilient, like a marathoner is tough. More like hard, like an AP calculus test is tough.  Not hard, like a block of concrete is hard.  Hard, as in difficult.  Eh, nevermind.

A colleague of mine just sent me a piece from the Miller-McCune site discussing a flawed mood study about September 11 pager text messages.

Researchers from Johannes Gutenberg University in Germany had concluded that there was an escalating level of “anger” words communicated to pagers as time passed on September 11 (here’s the study).  I’ve included the original data graph in this post. (more…)

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Sleuthing Out Questions about Hybrid Cars from Twitter

by May 20, 2011

It is hardly news that we are all paying a lot at to fill up our vehicles. As we prepare to launch a multi-week analysis of mood about gas prices (here’s the background on how we extract sentiment from tweets), I’m curious what questions people have that may have been sparked by high gas prices.

Questions around the topic of hybrid cars/vehicles seem like a good starting point, given that one of the key benefits of hybrids is the potential to cut down on fuel expenses. One goal could be to create something like this Wired flow chart that is designed to help people choose a social search site. Not sure yet what the starting question would be to draw in as many people as possible on the topic of hybrids, but I think it would need to be responsive to feeling pain at the pump. One can imagine an interactive flow chart that offered up explanatory videos at various decision points.

st_flowchart_social_f

So, what are people asking about hybrids on Twitter? Below is a sampling of what I observed from a quick search on the string “hybrids ?” (by the way, I’m impressed with Storify’s handy interface for creating this kind of graphic). (more…)

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Oil Companies’ Profits to Increase Greatly This Year; People’s Energy-Related Questions to Follow Suit.

by May 5, 2011

The rapid increase in oil prices should equate to the oil industry having its best year since 2008, as reported by Chris Kahn for AP (via ABC). Exxon Mobil Corp., Chevron Corp. and ConocoPhilips are expected to report a combined $18.2 billion in first quarter earnings — a 40% increase from last year and just shy of the $20.2 billion that they earned in the first three months of 2008.

An increase in consumption, the constriction of supply (e.g., Libya’s reserve access is currently limited), and also a weaker US dollar are all speculated to contribute to an increase in oil prices.

While some stand to benefit from the rise in oil prices (shareholders), businesses and consumers will feel the hurt as gasoline prices inflate. Increases in gas prices tend to have ripple effects, increasing the prices of transportation and any good or service that is reliant on transportation — bread, toiletries, DVD players, air plane tickets, etc.

The broad societal effect of an increase in oil prices is precisely what makes this issue of interest to Dialogue Earth.  This will undoubtedly augment expressed sentiment related to energy across social media platforms, such as Twitter. (more…)

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Just Around the Corner: A Longer-Running Pilot On Weather Emotions

by April 27, 2011

This week the weather in the U.S. has been pretty unusual. We set a record for rainfall here in the Twin Cities, which is really a footnote to the week compared to the violent extreme weather in the Southeast and beyond. While understanding how people are feeling about the weather day-to-day won’t change the weather, we see it as a great starting point for developing our Pulse system for tracking public opinion on issues discussed in the social media.

As a follow-on to our first weather pilot, we are gearing up to monitor mood about the daily weather across the U.S. for weeks at a time. In fact, we are just completing a run of about 8000 Twitter tweets through our “crowd-based sentiment engine” using the CrowdFlower platform. Once we have double-checked the results, we are set up now to collect tweets continuously, automatically send them over to CrowdFlower for sentiment judgments, have the judgments returned to our database automatically, and then publish the data on our interactive Pulse display. We expect to be analyzing several thousand tweets through CrowdFlower on a daily basis in order to create a detailed map of weather mood for the U.S. (see more here about our data sampling strategy). Look for more on this in the coming days. The image below is a sneak peek at our interactive platform, which our team has overhauled in recent weeks. It should prove to be a much-improved user experience!

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Global Warming Chatter: A Hot Topic on Twitter?

by March 28, 2011

Some months ago, our research team developed a strategy for inferring opinions about global warming from Twitter for our Pulse platform. We were lucky to be asked last week if we could present such data for the next issue of Momentum, the award-winning publication of the University of Minnesota’s Institute on the Environment. Of course, like all of us on a deadline, they needed it “yesterday.”

Not to be deterred, we rapidly spun up our collection system to grab those Twitter tweets that included the keywords global warming, climate change, and #climate. For a six day period ending on 23 March, we collected about 7600 tweets that had some geo-location information associated with them. Based on our recent experience focused on weather mood (described in this post), and because we had already generated a good number of quality control units (as described here), we posted a major job on the CrowdFlower platform within a day of the request from the Momentum team. Here’s a snapshot of the results:

momentum_dropshadow_300dpi (more…)

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Teasing Out Weather Mood From Twitter Posts: A Pulse Pilot

by March 8, 2011

In choosing a topic to use as a test case for our Pulse social media analytics tool, we wanted to pick something that is broadly discussed. What better topic to start with than people’s mood about the weather? It is hard to escape having a few thoughts about the weather on a regular basis. Snow storms, sunny warm days, and heatwaves, to mention a few, cross party lines and ideological divides. Plus, people love to discuss the weather, so we figured there would be lots of chatter in the social media—and we haven’t been disappointed. Read more on our weather strategy here.

In this post, I describe our first demonstration of the Pulse platform to describe weather mood across the U.S. using 12,500 tweets collected on February 4th. While our process is a work in progress, there are several key steps: identifying and collecting useful social media posts, getting reliable judgments about the sentiment in these posts made by crowd-sourced workers, publishing the data on our Pulse platform, and finally, combining our sentiment data with external data sources to tease out a story about the drivers of the observed sentiment.

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