Social Media « Another Word For It

February 28, 2016

NCSU Offers Social Media Archives Toolkit for Libraries [Defeating Censors]

Filed under: Instagram,Library,Library software,Social Media,Twitter — Patrick Durusau @ 8:19 pm

NCSU Offers Social Media Archives Toolkit for Libraries by Matt Enis.

From the post:

North Carolina State University (NCSU) Libraries recently debuted a free, web-based social media archives toolkit designed to help cultural heritage organizations develop social media collection strategies, gain knowledge of ways in which peer institutions are collecting similar content, understand current and potential uses of social media content by researchers, assess the legal and ethical implications of archiving this content, and develop techniques for enriching collections of social media content at minimal cost. Tools for building and enriching collections include NCSU’s Social Media Combine—which pre-assembles the open source Social Feed Manager, developed at George Washington University for Twitter data harvesting, and NCSU’s own open source Lentil program for Instagram—into a single package that can be deployed on Windows, OSX, and Linux computers.

“By harvesting social media data (such as Tweets and Instagram photos), based on tags, accounts, or locations, researchers and cultural heritage professionals are able to develop accurate historical assessments and democratize access to archival contributors, who would otherwise never be represented in the historical record,” NCSU explained in an announcement.

“A lot of activity that used to take place as paper correspondence is now taking place on social media—the establishment of academic and artistic communities, political organizing, activism, awareness raising, personal and professional interactions,” Jason Casden, interim associate head of digital library initiatives, told LJ. Historians and researchers will want to have access to this correspondence, but unlike traditional letters, this content is extremely ephemeral and can’t be collected retroactively like traditional paper-based collections.

“So we collect proactively—as these events are happening or shortly after,” Casden explained.

…

I saw this too late today to install but I’m sure I will be posting about it later this week!

Do you see the potential of such tooling for defeating would-be censors of Twitter and other social media?

December 25, 2015

The Social-Network Illusion That Tricks Your Mind – (Terrorism As Majority Illusion)

Filed under: Networks,Social Media,Social Networks — Patrick Durusau @ 5:19 pm

The Social-Network Illusion That Tricks Your Mind

From the post:

One of the curious things about social networks is the way that some messages, pictures, or ideas can spread like wildfire while others that seem just as catchy or interesting barely register at all. The content itself cannot be the source of this difference. Instead, there must be some property of the network that changes to allow some ideas to spread but not others.

Today, we get an insight into why this happens thanks to the work of Kristina Lerman and pals at the University of Southern California. These people have discovered an extraordinary illusion associated with social networks which can play tricks on the mind and explain everything from why some ideas become popular quickly to how risky or antisocial behavior can spread so easily.

Network scientists have known about the paradoxical nature of social networks for some time. The most famous example is the friendship paradox: on average your friends will have more friends than you do.

This comes about because the distribution of friends on social networks follows a power law. So while most people will have a small number of friends, a few individuals have huge numbers of friends. And these people skew the average.

Here’s an analogy. If you measure the height of all your male friends. you’ll find that the average is about 170 centimeters. If you are male, on average, your friends will be about the same height as you are. Indeed, the mathematical notion of “average” is a good way to capture the nature of this data.

But imagine that one of your friends was much taller than you—say, one kilometer or 10 kilometers tall. This person would dramatically skew the average, which would make your friends taller than you, on average. In this case, the “average” is a poor way to capture this data set.
…

If that has you interested, see:

The Majority Illusion in Social Networks by Kristina Lerman, Xiaoran Yan, Xin-Zeng Wu.

Abstract:

Social behaviors are often contagious, spreading through a population as individuals imitate the decisions and choices of others. A variety of global phenomena, from innovation adoption to the emergence of social norms and political movements, arise as a result of people following a simple local rule, such as copy what others are doing. However, individuals often lack global knowledge of the behaviors of others and must estimate them from the observations of their friends’ behaviors. In some cases, the structure of the underlying social network can dramatically skew an individual’s local observations, making a behavior appear far more common locally than it is globally. We trace the origins of this phenomenon, which we call “the majority illusion,” to the friendship paradox in social networks. As a result of this paradox, a behavior that is globally rare may be systematically overrepresented in the local neighborhoods of many people, i.e., among their friends. Thus, the “majority illusion” may facilitate the spread of social contagions in networks and also explain why systematic biases in social perceptions, for example, of risky behavior, arise. Using synthetic and real-world networks, we explore how the “majority illusion” depends on network structure and develop a statistical model to calculate its magnitude in a network.

Research has not reached the stage of enabling the manipulation of public opinion to reflect the true rarity of terrorist activity in the West.

That being the case, being factually correct that Western fear of terrorism is a majority illusion isn’t as profitable as product tying to that illusion.

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December 1, 2015

November 5, 2015

BEOMAPS:…

Filed under: Social Media,Topic Maps — Patrick Durusau @ 4:49 pm

BEOMAPS: Ad-hoc topic maps for enhanced search in social network data. by Peter Dolog, Martin Leginus, and ChengXiang Zhai.

From the webpage:

…
The aim of this project is to develop a novel system – a proof of concept that will enable more effective search, exploration, analysis and browsing of social media data. The main novelty of the system is an ad-hoc multi-dimensional topic map. The ad-hoc topic map can be generated and visualized according to multiple predefined dimensions e.g., recency, relevance, popularity or location based dimension. These dimensions will provide a better means for enhanced browsing, understanding and navigating to related relevant topics from underlying social media data. The ad-hoc aspect of the topic map allows user-guided exploration and browsing of the underlying social media topics space. It enables the user to explore and navigate the topic space through user-chosen dimensions and ad-hoc user-defined queries. Similarly, as in standard search engines, we consider the possibility of freely defined ad-hoc queries to generate a topic map as a possible paradigm for social media data exploration, navigation and browsing. An additional benefit of the novel system is an enhanced query expansion to allow users narrow their difficult queries with the terms suggested by an ad-hoc multi-dimensional topic map. Further, ad-hoc topic maps enable the exploration and analysis of relations between individual topics, which might lead to serendipitous discoveries.
…

This looks very cool and accords with some recent thinking I have been doing on waterfall versus agile authoring of topic maps.

The conference paper on this project is lodged behind a paywall at:

Beomap: Ad Hoc Topic Maps for Enhanced Exploration of Social Media Data, with this abstract:

Social media is ubiquitous. There is a need for intelligent retrieval interfaces that will enable a better understanding, exploration and browsing of social media data. A novel two dimensional ad hoc topic map is proposed (called Beomap). The main novelty of Beomap is that it allows a user to define an ad hoc semantic dimension with a keyword query when visualizing topics in text data. This not only helps to impose more meaningful spatial dimensions for visualization, but also allows users to steer browsing and exploration of the topic map through ad hoc defined queries. We developed a system to implement Beomap for exploring Twitter data, and evaluated the proposed Beomap in two ways, including an offline simulation and a user study. Results of both evaluation strategies show that the new Beomap interface is better than a standard interactive interface.

It has attracted 224 downloads as of today so I would say it is a popular chapter on topic maps.

I have contacted the authors in an attempt to locate a copy that isn’t behind a paywall.

Enjoy!

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November 2, 2015

#OpKKK Engaged: … [Dangers of skimming news]

Filed under: Government,Social Media — Patrick Durusau @ 7:30 pm

#OpKKK Engaged: Anonymous Begins Exposing Politicians with Ties to the KKK by Matt Agorist.

From the post:

Over the last week, the hacktivist group known as Anonymous has been saying that they will expose some 1,000 United States politicians who have ties to the KKK.

On Monday morning, just past midnight, the hackers made true on their “threat.”

In a video posted to the We are Anonymous Facebook page Monday, the group began to release the names of those they claim have ties to the KKK.

In the video, Anonymous states that they are not going to release the home addresses of the politicians in fear of violent retaliation against the accused racists. But the group did release the politicians’ full name, the municipalities in which they work, and the addresses of their political offices.

While the video doesn’t come close to the promised 1,000 names, Anonymous did release a partial list.

It is rumored that Anonymous plans to release all the names on the 5th of November, also known as Guy Fawkes Night. Anonymous is synonymous with Guy Fawkes as the popular mask is used to shield the faces of its members during their broadcasts and protests.
…

I must admit I had my own doubts about #OpKKK when I heard the number “1,000.”

That illustrates the danger of half-listening or skimming a news feed.

The number was surely higher than “1,000.”

Turns out that #OpKKK means a direct connection to the KKK and not just supporting their policies. That was my mistake. Just supporting KKK objectives, the number would be far higher.

Take that as a lesson to read carefully when going through news stories.

Failure to release addresses

The failure to release addresses of those named, “so nobody gets it in their mind to take out their own justice against them” is highly questionable.

Who does Anonymous think is going to administer “justice?”

With 1,000 political leaders having direct ties to the KKK, who in the government will call them to account?

The position of Anonymous reminds me of Wikileaks, the Guardian and the New York Times failing to release all of the Snowden documents and other government document dumps in full.

“Oh, oh, we are afraid to endanger lives.” Really? The government from who those documents were liberated has not hesitated to murder, torture and blight the lives of hundreds of thousands if not millions.

Rather than giving the people legitimate targets for at least some of those mis-deeds, you wring your hands and worry about possible collateral damage?

Sorry, all social change invovles collateral damage to innocents. Why do you think it doesn’t? The current systematic and structural racism exacts a heavy toll on innocents every day in the United States. Is that more acceptable because you don’t have blood on your hands from it? (Or don’t think you do.)

The term for that is “moral cowardice.”

Is annoying the status quo, feeling righteous, associating with other “righteous” folk, all there is to your view of social change?

If it is, welcome to the status quo from here to eternity.

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October 18, 2015

Tracie Powell: “We’re supposed to challenge power…

Filed under: Government,Journalism,Social Media — Patrick Durusau @ 10:01 pm

Tracie Powell: “We’re supposed to challenge power…it seems like we’ve abdicated that to social media” by Laura Hazard Owen.

From the post:

Tracie Powell tries not to use the word “diversity” anymore.

“When you talk about diversity, people’s eyes glaze over,” Powell, the founder of All Digitocracy, told me. The site covers tech, policy, and the impact of media on communities that Powell describes as “emerging audiences” — people of color and of different sexual orientations and gender identities.

I first heard Powell speak at the LION conference for hyperlocal publishers in Chicago earlier this month, where she stood in front of the almost entirely white audience to discuss how journalists and news organizations can get better at reporting for more people.

I followed up with Powell, who is currently a John S. Knight Journalism Fellow at Stanford, to hear more. “If we [as journalists] don’t do a better job at engaging with these audiences, we’re dead,” Powell said. “Our survival depends on reaching these emerging audiences.”

Here’s a lightly condensed and edited version of our conversation.

Warning: Challenging power is far more risky than supporting fiery denunciations of the most vulnerable and least powerful in society.

From women facing hard choices about pregnancy, rape victims, survivors of abuse both physical and emotional, or those who have lived with doubt, discrimination and deprivation as day to day realities, victims of power aren’t hard to find.

One of the powers that needs to be challenged is the news media itself. Take for example the near constant emphasis on gun violence and mass shootings. If you were to take the news media at face value, you would be frightened to go outside.

But, a 2013 Pew Center Report, Gun Homicide Rate Down 49% Since 1993 Peak; Public Unaware tell a different tale:

Not as satisfying as taking down a representative or senator but in the long run, influencing the mass media may be a more reliable path to challenging power.

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August 21, 2015

May 21, 2015

Twitter As Investment Tool

Filed under: Social Media,Social Networks,Social Sciences,Twitter — Patrick Durusau @ 12:44 pm

Social Media, Financial Algorithms and the Hack Crash by Tero Karppi and Kate Crawford.

Abstract:

‘@AP: Breaking: Two Explosions in the White House and Barack Obama is injured’. So read a tweet sent from a hacked Associated Press Twitter account @AP, which affected financial markets, wiping out $136.5 billion of the Standard & Poor’s 500 Index’s value. While the speed of the Associated Press hack crash event and the proprietary nature of the algorithms involved make it difficult to make causal claims about the relationship between social media and trading algorithms, we argue that it helps us to critically examine the volatile connections between social media, financial markets, and third parties offering human and algorithmic analysis. By analyzing the commentaries of this event, we highlight two particular currents: one formed by computational processes that mine and analyze Twitter data, and the other being financial algorithms that make automated trades and steer the stock market. We build on sociology of finance together with media theory and focus on the work of Christian Marazzi, Gabriel Tarde and Tony Sampson to analyze the relationship between social media and financial markets. We argue that Twitter and social media are becoming more powerful forces, not just because they connect people or generate new modes of participation, but because they are connecting human communicative spaces to automated computational spaces in ways that are affectively contagious and highly volatile.

Social sciences lag behind the computer sciences in making their publications publicly accessible as well as publishing behind firewalls so I can report on is the abstract.

On the other hand, I’m not sure how much practical advice you could gain from the article as opposed to the volumes of commentary following the incident itself.

The research reminds me of Malcolm Gladwell, author of The Tipping Point and similar works.

While I have greatly enjoyed several of Gladwell’s books, including the Tipping Point, it is one thing to look back and say: “Look, there was a tipping point.” It is quite another to be in the present and successfully say: “Look, there is a tipping point and we can make it tip this way or that.”

In retrospect, we all credit ourselves with near omniscience when our plans succeed and we invent fanciful explanations about what we knew or realized at the time. Others, equally skilled, dedicated and competent, who started at the same time, did not succeed. Of course, the conservative media (and ourselves if we are honest), invent narratives to explain those outcomes as well.

Of course, deliberate manipulation of the market with false information, via Twitter or not, is illegal. The best you can do is look for a pattern of news and/or tweets that result in downward changes in a particular stock, which then recovers and then apply that pattern more broadly. You won’t make $millions off of any one transaction but that is the sort of thing that draws regulatory attention.

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May 9, 2015

Exposure to Diverse Information on Facebook [Skepticism]

Filed under: Facebook,News,Opinions,Social Media,Social Networks,Social Sciences — Patrick Durusau @ 3:06 pm

Exposure to Diverse Information on Facebook by Eytan Bakshy, Solomon Messing, Lada Adamicon.

From the post:

As people increasingly turn to social networks for news and civic information, questions have been raised about whether this practice leads to the creation of “echo chambers,” in which people are exposed only to information from like-minded individuals [2]. Other speculation has focused on whether algorithms used to rank search results and social media posts could create “filter bubbles,” in which only ideologically appealing content is surfaced [3].

Research we have conducted to date, however, runs counter to this picture. A previous 2012 research paper concluded that much of the information we are exposed to and share comes from weak ties: those friends we interact with less often and are more likely to be dissimilar to us than our close friends [4]. Separate research suggests that individuals are more likely to engage with content contrary to their own views when it is presented along with social information [5].

Our latest research, released today in Science, quantifies, for the first time, exactly how much individuals could be and are exposed to ideologically diverse news and information in social media [1].

We found that people have friends who claim an opposing political ideology, and that the content in peoples’ News Feeds reflect those diverse views. While News Feed surfaces content that is slightly more aligned with an individual’s own ideology (based on that person’s actions on Facebook), who they friend and what content they click on are more consequential than the News Feed ranking in terms of how much diverse content they encounter.
…

The Science paper: Exposure to Ideologically Diverse News and Opinion

The definition of an “echo chamber” is implied in the authors’ conclusion:

…
By showing that people are exposed to a substantial amount of content from friends with opposing viewpoints, our findings contrast concerns that people might “list and speak only to the like-minded” while online [2].
…

The racism of the Deep South existed in spite of interaction between whites and blacks. So “echo chamber” should not be defined as association of like with like, at least not entirely. The Deep South was a echo chamber of racism but not for a lack of diversity in social networks.

Besides lacking a useful definition of “echo chamber,” the author’s ignore the role of confirmation bias (aka “backfire effect”) when confronted with contrary thoughts or evidence. To some readers seeing a New York Times editorial disagreeing with their position, can make them feel better about being on the “right side.”

That people are exposed to diverse information on Facebook is interesting, but until there is a meaningful definition of “echo chambers,” the role Facebook plays in the maintenance of “echo chambers” remains unknown.

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March 16, 2015

Bias? What Bias?

Filed under: Bias,Facebook,Social Media,Social Sciences,Twitter — Patrick Durusau @ 6:09 pm

Scientists Warn About Bias In The Facebook And Twitter Data Used In Millions Of Studies by Brid-Aine Parnell.

From the post:

Social media like Facebook and Twitter are far too biased to be used blindly by social science researchers, two computer scientists have warned.

Writing in today’s issue of Science, Carnegie Mellon’s Juergen Pfeffer and McGill’s Derek Ruths have warned that scientists are treating the wealth of data gathered by social networks as a goldmine of what people are thinking – but frequently they aren’t correcting for inherent biases in the dataset.

If folks didn’t already know that scientists were turning to social media for easy access to the pat statistics on thousands of people, they found out about it when Facebook allowed researchers to adjust users’ news feeds to manipulate their emotions.

…

Both Facebook and Twitter are such rich sources for heart pounding headlines that I’m shocked, shocked that anyone would suggest there is bias in the data! 😉

Not surprisingly, people participate in social media for reasons entirely of their own and quite unrelated to the interests or needs of researchers. Particular types of social media attract different demographics than other types. I’m not sure how you could “correct” for those biases, unless you wanted to collect better data for yourself.

Not that there are any bias free data sets but some are so obvious that it hardly warrants mentioning. Except that institutions like the Brookings Institute bump and grind on Twitter data until they can prove the significance of terrorist social media. Brookings knows better but terrorism is a popular topic.

Not to make data carry all the blame, the test most often applied to data is:

Will this data produce a result that merits more funding and/or will please my supervisor?

I first saw this in a tweet by Persontyle.

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March 7, 2015

February 24, 2015

January 1, 2015

December 14, 2014

Everything You Need To Know About Social Media Search

Filed under: Facebook,Instagram,Social Media,Twitter — Patrick Durusau @ 7:07 pm

Everything You Need To Know About Social Media Search by Olsy Sorokina.

From the post:

For the past decade, social networks have been the most universally consistent way for us to document our lives. We travel, build relationships, accomplish new goals, discuss current events and welcome new lives—and all of these events can be traced on social media. We have created hashtags like #ThrowbackThursday and apps like Timehop to reminisce on all the past moments forever etched in the social web in form of status updates, photos, and 140-character phrases.

Major networks demonstrate their awareness of the role they play in their users’ lives by creating year-end summaries such as Facebook’s Year in Review, and Twitter’s #YearOnTwitter. However, much of the emphasis on social media has been traditionally placed on real-time interactions, which often made it difficult to browse for past posts without scrolling down for hours on end.

The bias towards real-time messaging has changed in a matter of a few days. Over the past month, three major social networks announced changes to their search functions, which made finding old posts as easy as a Google search. If you missed out on the news or need a refresher, here’s everything you need to know.
…

I suppose Olsy means in addition to search in general sucking.

Interested tidbit on Facebook:

…
This isn’t Facebook’s first attempt at building a search engine. The earlier version of Graph Search gave users search results in response to longer-form queries, such as “my friends who like Game of Thrones.” However, the semantic search never made it to the mobile platforms; many supposed that using complex phrases as search queries was too confusing for an average user.
…

Does anyone have any user research on the ability of users to use complex phrases as search queries?

I ask because if users have difficulty authoring “complex” semantics and difficulty querying with “complex” semantics, it stands to reason they may have difficulty interpreting “complex” semantic results. Yes?

If all three of those are the case, then how do we impart the value-add of “complex” semantics without tripping over one of those limitations?

Osly also covers Instagram and Twitter. Twitter’s advanced search looks like the standard include/exclude, etc. type of “advanced” search. “Advanced” maybe forty years ago in the early OPACs but not really “advanced” now.

Catch up on these new search features. They will provide at least a minimum of grist for your topic map mill.

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October 25, 2014

October 22, 2014

Web Apps in the Cloud: Even Astronomers Can Write Them!

Filed under: Astroinformatics,Social Media — Patrick Durusau @ 7:23 pm

Web Apps in the Cloud: Even Astronomers Can Write Them!

From the post:

Philip Cowperthwaite and Peter K. G. Williams work in time-domain astronomy at Harvard. Philip is a graduate student working on the detection of electromagnetic counterparts to gravitational wave events, and Peter studies magnetic activity in low-mass stars, brown dwarfs, and planets.

Astronomers that study GRBs are well-known for racing to follow up bursts immediately after they occur — thanks to services like the Gamma-ray Coordinates Network (GCN), you can receive an email with an event position less than 30 seconds after it hits a satellite like Swift. It’s pretty cool that we professionals can get real-time notification of stars exploding across the universe, but it also seems like a great opportunity to convey some of the excitement of cutting-edge science to the broader public. To that end, we decided to try to expand the reach of GCN alerts by bringing them on to social media. Join us for a surprisingly short and painless tale about the development of YOITSAGRB, a tiny piece of Python code on the Google App Engine that distributes GCN alerts through the social media app Yo.

If you’re not familiar with Yo, there’s not much to know. Yo was conceived as a minimalist social media experience: users can register a unique username and send each other a message consisting of “Yo,” and only “Yo.” You can think of it as being like Twitter, but instead of 140 characters, you have zero. (They’ve since added more features such as including links with your “Yo,” but we’re Yo purists so we’ll just be using the base functionality.) A nice consequence of this design is that the Yo API is incredibly straightforward, which is convenient for a “my first web app” kind of project.

…

While “Yo” has been expanded to include more content, the origin remains an illustration of the many meanings that can be signaled by the same term. In this case, the detection of a gamma-ray burst in the known universe.

Or “Yo” could mean it is time to start some other activity when received from a particular sender. Or even be a message composed entirely of “Yo’s” where different senders had some significance. Or “Yo’s” sent at particular times to compose a message. Or “Yo’s” sent to leave the impression that messages were being sent. 😉

So, does a “Yo” have any semantics separate and apart from that read into it by a “Yo” recipient?

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September 7, 2014

May 31, 2014

April 26, 2014

Social Media Mining: An Introduction

Filed under: Data Mining,Social Media — Patrick Durusau @ 6:38 pm

Social Media Mining: An Introduction by Reza Zafarani, Mohammad Ali Abbasi, and Huan Liu.

From the webpage:

The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. Understanding and processing this new type of data to glean actionable patterns presents challenges and opportunities for interdisciplinary research, novel algorithms, and tool development. Social Media Mining integrates social media, social network analysis, and data mining to provide a convenient and coherent platform for students, practitioners, researchers, and project managers to understand the basics and potentials of social media mining. It introduces the unique problems arising from social media data and presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining. Suitable for use in advanced undergraduate and beginning graduate courses as well as professional short courses, the text contains exercises of different degrees of difficulty that improve understanding and help apply concepts, principles, and methods in various scenarios of social media mining.

Another Cambridge University Press title that is available in pre-publication PDF format.

If you are contemplating writing a textbook, Cambridge University Press access policies should be one of your considerations in seeking a publisher.

You can download the entire books, chapters, and slides from Social Media Mining: An Introduction

Do remember that only 14% of the U.S. adult population uses Twitter. Whatever “trends” you extract from Twitter may or may not reflect “trends” in the larger population.

I first saw this in a tweet by Stat Fact.

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November 10, 2013

Are You A Facebook Slacker? (Or, “Don’t “Like” Me, Support Me!”)

Filed under: Facebook,Marketing,Psychology,Social Media — Patrick Durusau @ 8:09 pm

Their title reads: The Nature of Slacktivism: How the Social Observability of an Initial Act of Token Support Affects Subsequent Prosocial Action by Kirk Kristofferson, Katherine White, John Peloza. (Kirk Kristofferson, Katherine White, John Peloza. The Nature of Slacktivism: How the Social Observability of an Initial Act of Token Support Affects Subsequent Prosocial Action. Journal of Consumer Research, 2013; : 000 DOI: 10.1086/674137)

Abstract:

Prior research offers competing predictions regarding whether an initial token display of support for a cause (such as wearing a ribbon, signing a petition, or joining a Facebook group) subsequently leads to increased and otherwise more meaningful contributions to the cause. The present research proposes a conceptual framework elucidating two primary motivations that underlie subsequent helping behavior: a desire to present a positive image to others and a desire to be consistent with one’s own values. Importantly, the socially observable nature (public vs. private) of initial token support is identified as a key moderator that influences when and why token support does or does not lead to meaningful support for the cause. Consumers exhibit greater helping on a subsequent, more meaningful task after providing an initial private (vs. public) display of token support for a cause. Finally, the authors demonstrate how value alignment and connection to the cause moderate the observed effects.

From the introduction:

We define slacktivism as a willingness to perform a relatively costless, token display of support for a social cause, with an accompanying lack of willingness to devote significant effort to enact meaningful change (Davis 2011; Morozov 2009a).

From the section: The Moderating Role of Social Observability: The Public versus Private Nature of Support:

…we anticipate that consumers who make an initial act of token support in public will be no more likely to provide meaningful support than those who engaged in no initial act of support.

Four (4) detailed studies and an extensive review of the literature are offered to support the author’s conclusions.

The only source that I noticed missing was:

10 Two men went up into the temple to pray; the one a Pharisee, and the other a publican.

11 The Pharisee stood and prayed thus with himself, God, I thank thee, that I am not as other men are, extortioners, unjust, adulterers, or even as this publican.

12 I fast twice in the week, I give tithes of all that I possess.

13 And the publican, standing afar off, would not lift up so much as his eyes unto heaven, but smote upon his breast, saying, God be merciful to me a sinner.

14 I tell you, this man went down to his house justified rather than the other: for every one that exalteth himself shall be abased; and he that humbleth himself shall be exalted.

King James Version, Luke 18: 10-14.

The authors would reverse the roles of the Pharisee and the publican, to find the Pharisee contributes “meaningful support,” and the publican has not.

We contrast token support with meaningful support, which we define as consumer contributions that require a significant cost, effort, or behavior change in ways that make tangible contributions to the cause. Examples of meaningful support include donating money and volunteering time and skills.

If you are trying to attract “meaningful support” for your cause or organization, i.e., avoid slackers, there is much to learn here.

If you are trying to move beyond the “cheap grace” (Bonhoeffer)* of “meaningful support” and towards “meaningful change,” there is much to be learned here as well.

Governments, corporations, ad agencies and even your competitors are manipulating the public understanding of “meaningful support” and “meaningful change.” And acceptable means for both.

You can play on their terms and lose, or you can define your own terms and roll the dice.

Questions?

* I know the phrase “cheap grace” from Bonhoeffer but in running a reference to ground, I saw a statement in Wikipedia that Bonhoeffer learned that phrase from Adam Clayton Powell, Sr.. Homiletics have never been a strong interest of mine but I will try to run down some sources on sermons by Adam Clayton Powell, Sr.

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September 11, 2013

August 14, 2013

Social Remains Isolated From ‘Business-Critical’ Data

Filed under: Data Integration,Data Silos,Social Media — Patrick Durusau @ 2:29 pm

Social Remains Isolated From ‘Business-Critical’ Data by Aarti Shah.

From the post:

Social data — including posts, comments and reviews — are still largely isolated from business-critical enterprise data, according to a new report from the Altimeter Group.

The study considered 35 organizations — including Caesar’s Entertainment and Symantec — that use social data in context with enterprise data, defined as information collected from CRM, business intelligence, market research and email marketing, among other sources. It found that the average enterprise-class company owns 178 social accounts and 13 departments — including marketing, human resources, field sales and legal — are actively engaged on social platforms.

“Organizations have invested in social media and tools are consolidating but it’s all happening in a silo,” said Susan Etlinger, the report’s author. “Tools tend to be organized around departments because that’s where budgets live…and the silos continue because organizations are designed for departments to work fairly autonomously.”

Somewhat surprisingly, the report finds social data is often difficult to integrate because it is touched by so many organizational departments, all with varying perspectives on the information. The report also notes the numerous nuances within social data make it problematic to apply general metrics across the board and, in many organizations, social data doesn’t carry the same credibility as its enterprise counterpart. (emphasis added)

Isn’t the definition of a silo the organization of data from a certain perspective?

If so, why would it be surprising that different views on data make it difficult to integrate?

Viewing data from one perspective isn’t the same as viewing it from another perspective.

Not really a question of integration but of how easy/hard it is to view data from a variety of equally legitimate perspectives.

Rather than a quest for “the” view shouldn’t we be asking users: “What view serves you best?”

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July 9, 2013

AAAI – Weblogs and Social Media

Filed under: Artificial Intelligence,Blogs,Social Media,Tweets — Patrick Durusau @ 12:34 pm

Seventh International AAAI Conference on Weblogs and Social Media

Abstracts and papers from the Seventh International AAAI Conference on Weblogs and Social Media.

Much to consider:

Frontmatter: Six (6) entries.

Full Papers: Sixty-nine (69) entries.

Poster Papers: Eighteen (18) entries.

Demonstration Papers: Five (5) entries.

Computational Personality Recognition: Ten (10) entries.

Social Computing for Workforce 2.0: Seven (7) entries.

Social Media Visualization: Four (4) entries.

When the City Meets the Citizen: Nine (9) entries.

Be aware that the links for tutorials and workshops only give you the abstracts describing the tutorials and workshops.

There is the obligatory “blind men and the elephant” paper:

Blind Men and the Elephant: Detecting Evolving Groups in Social News

Abstract:

We propose an automated and unsupervised methodology for a novel summarization of group behavior based on content preference. We show that graph theoretical community evolution (based on similarity of user preference for content) is effective in indexing these dynamics. Combined with text analysis that targets automatically-identified representative content for each community, our method produces a novel multi-layered representation of evolving group behavior. We demonstrate this methodology in the context of political discourse on a social news site with data that spans more than four years and find coexisting political leanings over extended periods and a disruptive external event that lead to a significant reorganization of existing patterns. Finally, where there exists no ground truth, we propose a new evaluation approach by using entropy measures as evidence of coherence along the evolution path of these groups. This methodology is valuable to designers and managers of online forums in need of granular analytics of user activity, as well as to researchers in social and political sciences who wish to extend their inquiries to large-scale data available on the web.

It is a great paper but commits a common error when it notes:

Like the parable of Blind Men and the Elephant², these techniques provide us with disjoint, specific pieces of information.

Yes, the parable is oft told to make a point about partial knowledge, but the careful observer will ask:

How are we different from the blind men trying to determine the nature of an elephant?

Aren’t we also blind men trying to determine the nature of blind men who are examining an elephant?

And so on?

Not that being blind men should keep us from having opinions, but it should may us wary of how deeply we are attached to them.

Not only are there elephants all the way down, there are blind men before, with (including ourselves) and around us.

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April 23, 2013

March 6, 2013

February 4, 2013

The Swipp API: Creating the World’s Social Intelligence

Filed under: Social Graphs,Social Media,Social Networks — Patrick Durusau @ 11:29 am

The Swipp API: Creating the World’s Social Intelligence by Greg Bates.

From the post:

The Swipp API allows developers to integrate Swipp’s “Social Intelligence” into their sites and applications. Public information is not available on the API; interested parties are asked to email info@swipp.com. Once available the APIs will “make it possible for people to interact around any topic imaginable.”

[graphic omitted]

Having operated in stealth mode for 2 years, Swipp founders Don Thorson and Charlie Costantini decided to go public after Facebook’s release of it’s somewhat different competitor, the social graph. The idea is to let users rate any topic they can comment on or anything they can photograph. Others can chime in, providing an average rating by users. One cool difference: you can dislike something as well as like it, giving a rating from -5 to +5. According to Darrell Etherington at Techcrunch, the company has a three-pronged strategy of a consumer app just described, a business component tailored around specific events like the Superbowl, that will help businesses target specific segments.

A fact that seems to be lost in most discussions of social media/sites is that social intelligence already exists.

Social media/sites may assist in the capturing/recording of social intelligence but that isn’t the same thing as creating social intelligence.

It is an important distinction because understanding the capture/recording role enables us to focus on what we want to capture and in what way?

What we decide to capture or record greatly influences the utility of the social intelligence we gather.

Such as capturing how users choose to identify particular subjects or relationships between subjects, for example.

PS: The goal of Swipp is to create a social network and ratings system (like Facebook) that is open for re-use elsewhere on the web. Adding semantic integration to that social networks and ratings system would be a plus I would imagine.

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February 1, 2013

REVIEW: Crawling social media and depicting social networks with NodeXL [in 3 parts]

Filed under: NodeXL,Social Graphs,Social Media,Social Networks — Patrick Durusau @ 8:08 pm

REVIEW: Crawling social media and depicting social networks with NodeXL by Eruditio Loginquitas.appears in three parts: Part 1 of 3, Part 2 of 3 and Part 3 of 3.

From part 1:

Surprisingly, given the complexity of the subject matter and the various potential uses by researchers from a range of fields, “Analyzing…” is a very coherent and highly readable text. The ideas are well illustrated throughout with full-color screenshots.

In the introduction, the authors explain that this is a spatially organized book—in the form of an organic tree. The early chapters are the roots which lay the groundwork of social media and social network analysis. Then, there is a mid-section that deals with how to use the NodeXL add-on to Excel. Finally, there are chapters that address particular social media platforms and how data is extracted and analyzed from each type. These descriptors include email, thread networks, Twitter, Facebook, WWW hyperlink networks, Flickr, YouTube, and wiki networks. The work is surprisingly succinct, clear, and practical.

Further, it is written with such range that it can serve as an introductory text for newcomers to social network analysis (me included) as well as those who have been using this approach for a while (but may need to review the social media and data crawling aspects). Taken in total, this work is highly informative, with clear depictions of the social and technical sides of social media platforms.

From part 2:

One of the strengths of “Analyzing Social Media Networks with NodeXL” is that it introduces a powerful research method and a tool that helps tap electronic media and non-electronic social network information intelligently, in a way that does not over-state what is knowable. The authors, Derek Hansen, Ben Schneiderman, and Marc A. Smith, are no strangers to research or academic publishing, and theirs is a fairly conservative approach in terms of what may be asserted.

To frame what may be researched, the authors use a range of resources: some generalized research questions, examples from real-world research, and step-by-step techniques for data extraction, analysis, visualization, and then further analysis.

From part 3:

What is most memorable about “Analyzing Social Media Networks with NodeXL” is the depth of information about the various social network sites that may be crawled using NodeXL. With so many evolving social network platforms, and each capturing and storing information differently, it helps to know what an actual data extractions mean.

I haven’t seen the book personally, but from this review it sounds like a good model for technical writing for a lay audience.

For that matter, a good model for writing about topic maps for a lay audience. (Many of the issues being similar.)

Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

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