May 15, 2013
Do not get the pitchforks and torches ready, instead set a countdown clock and wait for the explosion! The Verge tells us that you can “Give Tweets A Death Sentence With Efemr.” Efemr is a web app that gives tweets a time limit and then it is permanently deleted. The idea is replicating SnapChat’s popular idea: snap a photo, add destruction time, and it is lost to the ages. Once you download Efemr, you give it access to your Twitter account and you create the time limit with hash tags.
Despite the momentary life span of its content, Efemr has a purpose:
“The web app is advertised as a means of making your Twitter activity more fleeting, but also as a tool to “protect your e-reputation.” That latter point is somewhat questionable, since all it takes is a retweet to ruin any attempt to cover your tracks on the popular service. SnapChat has shown there’s demand for this type of erasable social media, though we’re not convinced trying to shoehorn the concept within Twitter is a good strategy.”
The demand is that people want these social media Web tools to be more life real conversation, momentary and fleeting. Social media documents everything and leaves visible evidence that used to disappear. The Library of Congress will not like that, because when the tweet “goes boom” there is nothing to search for.
Whitney Grace, May 15, 2013
April 22, 2013
As social media outlets such as Twitter continue to grow analysts can tell a lot from what users are tweeting or which topics have the most followers. It seems that Big Data is really buzzing in the Twitter world and created quite a stir in 2012. According to the DataSift article “Who’s Big in Big Data? the data science team at DataSift did an analysis of the amount of social interaction that Big Data received in 2012.
“A record number of Tweets were reported relating to big data within the technology sector in 2012 showing a continual growth of social interaction around ‘Big Data’. Using our sophisticated social data platform, we ran a DataSift Historics query against our hot list of Big Data products and conversations to identify which vendors were the most socially interactive, which domains were the most favorable in publicizing ’Big Data’ Tweets, the quarterly traffic progression for mentions of ‘Big Data’ and the most Tweeted stories.”
From the comparison of the various Tweets concerning Big Data, DataSift was able to determine which topics were the most popular. They then went a step further and looked at which links people shared and what Big Data sites people went to the most. Results showed that over 2.2 million Tweets were generated and Apache was the most popular Big Data vendor. As an added bonus DataSift also was delighted to learn that a BBC news article on DataSift took 2nd place in the running for most shared Big Data stories of 2012. This type of social media analysis not only provides companies with valuable insight for their daily business but also shows who the heavy hitters really are in the Big Data world.
April Holmes, April 22, 2013
March 17, 2013
Several of the goslings have been in contact with Twitter. So far the teen age funster continues to use this somewhat unexciting blog to disseminate information about various activities of little interest to a 69 year old or the librarians assisting me. We will keep you informed but for now, just unfollow the Beyond Search stream on Twitter. What’s interesting is that Twitter is “trying” to assist us. Hmm.
Stephen E Arnold, March 17, 2013, 9 30 am Eastern
March 11, 2013
Real-time tools are used to record information that corresponds directly to actual life. One of the best examples of real-time information is the social networking tool Twitter. CNET wrote an article about Twitter’s time fallacy, “Time Calculator Shows Futility In Trying To Keep Up With Twitter.” The article mentions that in small doses, Twitter is a great tool to keep updated on information, but if can make someone instance trying to follow it all the time. If you feel like life is passing you by if you cannot keep up with tweets, then web developer Koobazaur created the Tweetulator. The Tweetutular calculates how much time you would need to read every single tweet on your feed.
You input the number of people you follow, reading speed, and number of tweets you read a day. For example Twitter co-founder Jack Dorsey would need fourteen hours each day to keep up with the 1330 people he follows.
“The Tweetulator results aren’t really that surprising, but it does manage to put Twitter time into perspective. Let’s just say that if I miss a few tweets here and there, I’m not going to feel bad about it.”
Let us say there is more to life than Twitter and time can be better spent developing new enterprise search strategies.
Whitney Grace, March 11, 2013
February 25, 2013
Twitter, now with more tweets! I suppose that’s a real plus for some. ComputerWorld announces, “Twitter Search to Show Tweets More Than a Week Old.” Writer Jeremy Kirk explains:
“Twitter is modifying its search engine to include tweets more than a week old, a move it said will help users uncover better content.
“Over the next few days, searches will return ‘a fairly small percentage of total tweets ever sent’ but that will increase over time, wrote Paul Burstein, an engineer who works on Twitter’s search infrastructure, on a company blog.
“‘We look at a variety of types of engagement, like favorites, retweets and clicks, to determine which tweets to show,’ Burstein wrote. ‘We’ll be steadily increasing this percentage over time, and ultimately, aim to surface the best content for your query.’”
I suppose a wider search results field is better, whatever the platform. The expansion was announced alongside Twitter‘s updates to its search function in its iOS and Android mobile apps. These apps now return tweets, photos, and people in a single results stream rather than separate tabs. One other change saves users a step by letting them go directly to a linked Web site without opening the corresponding tweet. Ah, the relentless march of progress—now saving us a few seconds at a time.
Cynthia Murrell, February 25, 2013
February 22, 2013
Twitter’s blog post, “Search and Discover Improvements: Get More Great Content Faster,” describes updates to the service’s Android and iOS apps and to its mobile-tailored Web address . The primary change, as revealed by product management director Esteban Kozak, is the implementation of separate tabs with their own content streams.
There four of these distinct streams— Discover, Search, Connect, and Links. It is the first two that we find most interesting. The write-up specifies:
“Discover: Now all the content in Discover — Tweets, Activity, Trends and suggestions of accounts to follow — appears in a single stream, on both iPhone and Android. You can also dive into Activity and Trends from new previews at the top of the Discover tab.
“Search: Search results now surface the most relevant mix of Tweets, photos, and accounts, all in one stream (similar to the stream in Discover). We’ve also added a new search button to Twitter for iPhone, letting you search from anywhere within the app. (This button was already available in the Android and iPad apps.) Look for the magnifying glass icon next to the button you use to compose a Tweet.”
Making search and discovery easier to find and use is a worthy goal, and usually fairly straightforward to implement. The quality of search results, it should be remembered, is another matter entirely. The post mentions that information on new developments can always be found within Twitter’s entries at the App Store and Google Play.
Cynthia Murrell, February 22, 2013
February 9, 2013
ChaCha keeps on getting money. We learn about the outfit’s latest round of funding in All Things D’s piece, “ChaCha, Still Grinding Away at This Online Q&A Thing, Raises Another $14M.” Like Coveo ,it appears that ChaCha’s intake of investment is not yet generating an output of profit. Is its big pay day just around the corner?
Writer Liz Gannes sees the pattern, too, noting that the firm has now collected $82 million in funding. She reports that CEO Scott Jones believes his company has almost, after a history of ups and downs, conquered the Q&A conundrum. The key points: transitioning from the use of paid answerers to “passionate” (volunteer), identifiable sources; emphasizing social distribution over search; and offering brand-names the chance to share their wisdom, for a fee of course. Gannes writes:
“So: After clashing with Google by gaming its search results, ChaCha wants to take the even harder path of competing with Google head on, by trying to better answer the sort of quick questions Google now surfaces on results pages through its ‘Knowledge Graph.’
“But Jones said ChaCha can go further than Google because it has spent years focusing on how to answer ‘out and about’ questions about surroundings, make judgment calls and recommendations, and process phrasings that evade natural linguistic processing.
“And, in the meantime, ChaCha has built up an audience of 45 million uniques per month and two billion questions answered.”
Not too shabby, especially considering the setback the company experienced when it tangled with Google’s Panda in 2011. ChaCha has also found success with its “sponsored tweet scheme” Social Reactor, which pays out up to $100,000 per month to contracted tweeters. The distribution power associated with that program, says Jones, will help when the company pushes more forcefully into the mobile-app realm later this year. Let us hope ChaCha finds success soon; I’m sure their investors do.
ChaCha‘s free “ask-a-smart-friend” answer service can be accessed at chacha.com or through their mobile app. The company was formed in 2005, and currently employs 70 individuals. ChaCha is headquartered in Carmel, Indiana, just north of Indianapolis.
Cynthia Murrell, February 09, 2013
February 4, 2013
While the term big data has been around for quite some time now as a commonly used phrase, there are still some media sources exploring the story and lineage behind the term used today. The New York Times‘ recent article “The Origins of ‘Big Data’: An Etymological Detective Story” delves into the subject, but first presents a staggering fact.
The Library of Congress announced last month that their directory of public tweets had reached 170 billion and this number is only rising. Because of a deal between Twitter and the Library, these tweets are not yet available for researchers to use, but this shows how connected both people and businesses are to big data.
From economists to John Mashey, the author explores possibilities of who should be credited with the origin of big data:
In the 1990s, Silicon Graphics was the giant of computer graphics, used for special-effects in Hollywood and for video surveillance by spy agencies. It was a hot company in the Valley that dealt with new kinds of data, and lots of it. There are no academic papers to support the attribution to Mr. Mashey. Instead, he gave hundreds of talks to small groups in the middle and late 1990s to explain the concept and, of course, pitch Silicon Graphics products.
While the story of big data’s origin is an interesting one, what is more exciting to businesses today are the possibilities for ROI. Technologies such as PolySpot that are designed to increase productivity and efficiency in the workplace are helping organizations achieve competitive advantage.
Megan Feil, February 4, 2013
Sponsored by ArnoldIT.com, developer of Beyond Search.
January 31, 2013
As with any technology, different people use Twitter differently. Forbes breaks this diversity down into “The 10 Types of Twitterers and How to Tame Their Tweets.” To set the stage, writer Steve Faktor explains why it is a mistake to label Twitter a social network:
“Though it looks social, it’s more hyperactive than interactive. Of the billions of tweets sent, 71% get no response, only 36% are worth reading, and a majority is generated by a tiny fraction of users. Twitter is a personal announcement system that captures the collective pulse of a world screaming for attention – or revolution, or discounts, or Kanye. Twitter is a tiny, evolutionary step towards a ‘global mind’. Making sense of that mind has spurred a gold rush of mind-readers trying to sell you shovels, pans, and a donkey.”
With that, the article launches into the Twitter-type descriptors. On one end of the scale, you have what Faktor colorfully calls the “undead,” those 60 percent of accounts that were created but remain inactive. “Organizations,” large corporations that Faktor calls Twitter’s big spenders like Starbucks and Zappos, are at the other end. It seems that most businesses, though, have so far failed to recoup big bucks this way. In the middle are such characters as “chirpers,” “scouts,” and “stars.” It is worth reading through his astute descriptions.
The write-up also lists three types of incentives that motivate tweeters: The tangible, like discounts or job leads; the perceived, psychological rewards like respect or convenience; and the informational, actionable data that feels rewarding. Will other incentives manifest? Twitter is still an evolving medium, and its use is a continuing experiment. I wonder what a list of user types will look like five or ten years from now.
Cynthia Murrell, January 31, 2013
January 10, 2013
Since its famous role in the Arab Spring, Twitter‘s status as an active participant in (as opposed to simply a documenter of) unfolding events has been self-evident. Since then, on several notable occasions, users of the service have supplied crucial information before traditional news sources got their hands on the facts. However, as we saw during the tragic events of December 14, sometimes Twitter users get it wrong. Sometimes, the misinformation causes unnecessary stress, confusion, and even danger. That’s quite a downside to the otherwise helpful contrivance. What is a concerned citizen of the world to believe?
A solution may be on the way. It is after the fact (this time), but it is progress nevertheless. Slate’s “Building a Better Truth Machine” examines the possibility that machine-learning algorithms could identify and halt false rumors before they pervade the Twittersphere. Several studies have recently emerged that identify common characteristics of both true and false tweets. (See here and here for a couple of examples supplied by the article.) Writer Will Oremus tells us:
The authors of the 2010 study [from Yahoo Research, here] developed a machine-learning classifier that uses 16 features to assess the credibility of newsworthy tweets. Among the features that make information more credible:
- Tweets about it tend to be longer and include URLs.
- People tweeting it have higher follower counts.
- Tweets about it are negative rather than positive in tone.
- Tweets about it do not include question marks, exclamation marks, or first- or third-person pronouns.
Several of those findings were echoed in another recent study from researchers at India’s Institute of Information Technology who also found that credible tweets are less likely to contain swear words and significantly more likely to contain frowny emoticons than smiley faces.
Interesting. Oremus admits that those looking to purposely spread lies are sure to find a way around any algorithm that may be put in place, but suspects that it would at least cut down on the proliferation of inaccuracies. Let us hope that he is correct, and that an effective solution is implemented soon.
Cynthia Murrell, January 10, 2013