Why Twitter Is the Low-Hanging Fruit of Social Analytics
Nobody is mistaking the Twitter fire hose for a crystal ball. But big companies are increasingly turning to Twitter and other social media outlets for a range analytic tasks, from gauging customer sentiment about bendy smartphones to saving costs during product recalls.
Corporations have been analyzing social media since it arrived on the scene year ago. But only recently have they figured out how to really make use of it, according to Katherine Matsumoto of Attensity, a big data analytics firm based in Salt Lake City.
“It’s really an under-tapped data source,” says Matsumoto, a natural language processing (NLP) expert. “We like to think of social media as being able to harvest the universe’s biggest consumer focus group. You can ask and answer any question you need.”
Attensity has parlayed its background in providing text analytics for big companies and the government into becoming a one-stop shop for social media analysis for the likes of Ebay, Yahoo, Microsoft, Verizon, and Whirlpool. The company provides a soup-to-nuts solution that lets non-technical users ask questions of the uber focus group that is social media and see results in real time. It exposes to its customers more than 550 million social media posts and tweets per day, including the entire Twitter fire hose via a contract with Gnip (now part of Twitter proper).
The company has done a lot of the standard social analytics fare, including answering questions such as “Does my new marketing message resonate with customers?” But Matsumoto has seen other more interesting use cases where companies find value in other ways, including identifying instances of fraud.
“We work with insurance companies that are working on cases where they can identify potential connections between product recalls and claims they’ve had to issue, where they might be able to avoid responsibility for paying for incidents that can be traced back to a recall,” she says. “That kind of information is just circulating.”
Even IBM is warming up to the low-hanging fruit that Twitter provides the world. Just last month, the century-old IT behemoth formed a partnership with Twitter whereby it will pipe the fire hose into enterprise accounts and help them mine it for useful data. IBM CEO Ginni Rometty applauded Twitter for creating “something extraordinary” and being able to “take the pulse of the planet.”
Hooking up with Twitter is a smart move on IBM’s part, says R “Ray” Wang, principal analyst and founder of Constellation Research.
“I think we’re starting to determine correlations from social signals,” Wang tells Datanami. “What IBM and other analytical players can do is identify potential linkages that can help predict next best actions. It takes a lot of data to crunch and it’s still possible for false positives and false negatives to emerge. However, businesses should treat these as strong signals to decision making not as [an end-all, be-all]. We still have to connect other data points and determine how strong these signals are.”
Another member of IT’s old guard that’s now embracing social analytics is FICO. Formerly Fair Isaac, the firm best known for building the tools for determining consumer credit scores last week announced it will be delivering a text analytic tool next quarter that can mine Twitter and other social properties for useful information.
“Enterprises are waking up to its significance and the technologies are getting easier to use,” says FICO’s Big Data Strategist Martin Hall, the founder of Karmashere, the Hadoop application developer that FICO bought earlier this year. “It’s clearly mainstream.”
While FICO didn’t divulge much about the forthcoming text analytics tool, the goal will be to enable customer to mine social media sites like Twitter and Facebook, as well as other sources, such as email. Given FICO’s expertise in the finical services business, it could also harness social media data to improve services it’s already providing customers, including fraud detection and determining credit scores.
“Twitter and Facebook are obviously good examples of semi-structured or unstructured data that can be harnessed in this new world of big data, where the platform itself, namely Hadoop, makes it possible and products like ours make it much easier for the practitioners–the data scientists, the analysts, and the business users–to actually go at that data, whatever it is,” Hall tells Datanami.
Much of the focus remains around customer sentiment, which is the original use case for social media leveraged by brand marketers. That means identifying positive and negative sentiment around not only your company, but your competitors. “If you can discover the negative sentiment and messages around competitors’ products, and you can combine that with positive sentiment about your own products, then that can inform the messages you use to target potential customers based on feedback from the marketplace,” Hall says.
Given the volumes of data, however, one must approach social media analytics somewhat carefully. There are 500 million Tweets made per day, but the vast majority of them will be worthless to you and your company.
Just the same, given the volume, there are jewels hidden in there available for the taking, says Mike Stringer, chief data scientist and co-founder of Datascope Analytics, a big data consulting firm based in Chicago.
“It is loads of crap, and the fire hose is so big that the fraction of non-crap is pretty small,” Stringer says. “But the absolute amount of non-crap is still a lot of good stuff. It’s the classic information retrieval problem around needles in the haystack. And with Twitter and the Internet, the haystack is really, really big, so there are a lot of needles.”
May 6, 2021
- Domino Data Lab Launches ‘Data Science Leaders’ Podcast with Insights on Enterprise MLOps
- Syniti New Global Data Value Report: Only 5% of Executives Trust their Enterprise Data
- BSC Uses Mobile Data to Capture Barcelona’s Mobility Patterns in Public-Private Partnership
- Datadobi Report Highlights Impact of Data Growth on Storage Management
May 5, 2021
- Domo Rated Exemplary Vendor in Ventana 2021 Embedded Analytics and Data Value Index
- StarTree Secures $24M Funding to Commercialize Analytics Platform
- SoftIron Announces HyperDrive Performance+ Family
- Sumo Logic Unveils Sumo Organizations for Managing Security Intelligence at Scale
- New Survey Shows Enterprises Adopting Kubernetes for Big Data Cloud Migration, Cost Reduction
- Splunk Launches New Observability Cloud
- HPE Expands GreenLake with Storage as-a-Service Business Transformation
- KX Partners with Microsoft to Take Streaming Analytics to the Cloud
- dotData Launches dotData Py Lite, Putting AI Automation on Every Data Scientist’s Laptop
- Precisely Announces Trust ’21 Data Integrity Summit
- Ariox Releases Lumino-A One-Stop Scalable Integration Solution
May 4, 2021
- AWS Announces General Availability of Amazon DevOps Guru
- Panoply Adds Square Native Connector to Growing List of Data Sources
- Privitar Launches Modern Data Provisioning Platform for Self-Service Data Access
- Hivemind Partners with Databricks to Drive Business Value with Unified Data Analytics
Most Read Features
- Big Data File Formats Demystified
- What’s the Difference Between AI, ML, Deep Learning, and Active Learning?
- Can Digital Twins Help Modernize Electric Grids?
- Composite AI: What Is It, and Why You Need It
- Who’s Winning In the $17B AIOps and Observability Market
- Understanding Your Options for Stream Processing Frameworks
- Big Data Predictions: What 2020 Will Bring
- Why Data Science Is Still a Top Job
- Is Python Strangling R to Death?
- 10 Big Data Statistics That Will Blow Your Mind
- More Features…
Most Read News In Brief
- Confluent Files to Go Public. Who Could Be Next?
- Data Prep Still Dominates Data Scientists’ Time, Survey Finds
- Dataiku Gets Closer to Snowflake
- Esri Simplifies Developer Access to Location Data with ArcGIS Platform
- Insightsoftware Loads Up on Embedded Analytics with Logi, Izenda Deals
- Global DataSphere to Hit 175 Zettabytes by 2025, IDC Says
- Nvidia’s Jarvis Offers Real-Time Machine Translation
- ML Scaling Requires Upgraded Data Management Plan
- Grafana Ditches Apache 2.0, Switches to AGPL
- Databricks Edges Closer to IPO with $1B Round
- More News In Brief…
Most Read This Just In
- Novel Use of 3D Geoinformation to Identify Urban Farming Sites
- Tecton Unveils Major New Release of Feast Open Source Feature Store
- KIOXIA’s PCIe 4.0 NVMe SSDs Now Qualified with NVIDIA Magnum IO GPUDirect Storage
- SC21: Introducing the [email protected] Data Science Competition
- Crayon Raises $22M Series B to Empower Enterprises with Competitive Intelligence
- Gartner Highlights 3 Actions for Data and Analytics Leaders to Succeed in a Changing World
- Domino Data Lab Debuts New Solutions with NVIDIA to Enhance the Productivity of Data Scientists
- Crate.io Expands CrateDB Cloud with the Launch of CrateDB Edge
- Alteryx Global Inspire 2021 Conference to Showcase New Products in Analytics and Data Science
- Splunk Launches New Observability Cloud
- More This Just In…
Sponsored Partner Content
May 13 @ 11:00 am - 12:30 pm