LOLspeak study

I have been arguing for a while that LOLcats belong in graduate courses and they are worthy of scholarly research.

So, here is a presentation about the linguistic study of LOLspeak (the language cats speak). It is analyzed as language play that has a function in the construction of online identity – as a cat and Internet savvy person.

 

I can has language play: Construction of Language and Identity in LOLspeak from Lauren Gawne on Vimeo.

New research project: Managing identity & social groups across social networking sites

My latest research project builds on previous work about online identity management and seeks to further understand how active social media users manage their identity and social groups across multiple social networking sites (e.g. Facebook, Twitter, LinkedIn, Google+).

We are looking for volunteers to participate in research interviews. Interviews will take about 30 minutes, and will be conducted via telephone or Skype.

Specifically, we are searching for individuals who meet the following criteria:

• Has graduated from college within the past two years OR
• Is a social media consultant OR
• Is an IT security professional

AND

• Is an active social media user – participates actively in 3 or more social networking sites

In exchange for your time, you will have a 1 in 10 chance to win $25 in cash, gift card, or donation to your preferred charity.

Interested in participating? Please contact me through this online form.

Do you know other people who may wish to participate? Please forward them the link to this post.

Thank you,
Dr. V

This project is supported by a research grant from Verisign, Inc. Co-PI: Gene Spafford – CERIAS, Purdue University

Natural user interfaces, movement, and emotion (Google Talk)

A Purdue ENE student posted this video on Facebook, and after watching, I had to curate it here. The idea is so simple, and so brilliant – after seeing the video, all I can say is “duh! – it makes perfect sense!”

Here’s the brief summary:

• we have the technology to interface with computers using movement – aka Natural User Interfaces (NUI) – like Xbox Kinect.
• movement of the body is related to emotion – something yogis have known for a long time, and modern research is confirming. For example, an open, expansive, body posture will make you feel happy and powerful (see, for example, this research study). Also, body posture and movement have social implications – for example, moving in sync creates liking & trust.
• Therefore, we should create interfaces that invite open, expansive, fluid body movements, in order to increase positive affect (put people in a good mood).
• Possible applications: Gmail TaiChi – Using TaiChi movements to sort through your Inbox in the morning; OR: A serious game for learning math that requires open, expansive movement is likely to reduce math anxiety.
• DUH! Brilliant!

Watch Katherine Isbister‘s Google Talk to grasp the details of this argument, and to see applications and interesting research projects:

Online indentity management & social groups

I came across this presentation on John Bells’ blog (John Bell heads the Digital Influence Team at Ogilvy PR) and had to share it here.

This happens to be one of my research interests, something I alluded to in an earlier blog post, and I am now working to get ready for publication.

The presentation is from Paul Adams, senior UX researcher at Google. I love the connection he makes between social science and social interface/product design. I love the fact that this kind of research happens in a corporate setting, and if I didn’t love teaching so much I’d be jealous of his job.

Research article: Online influencers

There are many attempts in the industry (and many apps) to identify online influencers. My main concern with them is that they operate with a seat-of-the-pants operational definition of the concept of “influencer.” What are, exactly, the behaviors that characterize an influencer? And how do you know that the behaviors a certain app is measuring (e.g. number of followers and number of retweets on Twitter) are actually measuring social influence and not something else? We have seen that, according to such measures, Sockington the cat is more influential than Chris Brogan.

This is where academic research can help. I’m browsing the latest issue of Human Communication Research and came across this article:

Huffaker, D. (2010). Dimensions of leadership and social influence in online communities. Human Communication Research, 36(4), 593-617

[note: David Huffaker completed his Ph.D. at Northwestern and now he is a researcher at Google, according to his website. This paper was part of his dissertation work.]

The article set out to identify the communication traits of online leaders (aka influencers, but influencer is not a word, so it can’t be used in an academic publication). These communication traits are of two types: (1) linguistic characteristics; and (2) social interaction patterns.

To identify influencers’ communication traits, Huffaker used both automated textual analysis and social network analysis.

Drawing on previous literature on leaders in the offline world and opinion leaders, Huffaker proposes the following abilities that define online leaders: The ability to:

• trigger feedback
• spark conversations within the community
• shape the way other members of a group discuss a topic

in other words, they…

• set agendas for discussion by causing or facilitating dialog on a particular topic
• frame discussion by shaping the way a topic is talked about

The study was designed to examine the relationship between 3 characteristics of online leaders and online leadership itself. If there is a strong relationship, this means that the 3 characteristics are good indicators of online leadership. So, the 3 characteristics were the independent variables, and online leadership was the dependent variable:

Independent variables:

1. communication activity (measured as: number of posts a person has contributed to a group; number of replies a person contributes to messages initiated by other group members; length of participation in the community, as an indication of credibility)
2. social networks (measured as: expansiveness – the number of times a person replies to different group members; reciprocity – frequency of a person’s participation in a back-and-forth dialog with another person; brokering – being the link between two otherwise unrelated groups)
3. language use (measured as: talkativeness – the average length of messages contributed by a person; linguistic diversity – the number of unique words found in a message; assertiveness – frequency of certain words indicating assertiveness, such as “always” and “never;” affect – frequency of words that represent emotional language, such as “nice,” “ugly,” “happy,” etc.

Dependent variable: online leadership, operationalized (measured) as:

• reply trigger – the ability to inspire responses
• conversation creation – the ability to spark a long dialog between users
• language diffusion – measured as the number of words used by the author of a message that were repeated by other users in subsequent replies (so, if A triggers a discussion using the word “inappropriate,” if the same word is used frequently in other posts on the topic, this indicates high language diffusion, and therefore, social influence

The author used linguistic analysis(LIWC)  and social network analysis (UCINET) software and performed the analyses on a random sample of 16 Google Groups on various topics. The sample included 33,540 users and 632,622 messages written between June 21, 2003-January 31, 2005.

The measures of the independent and dependent variables were analyzed using correlations, regression analysis, and hierarchical linear modeling analysis (I wish I could explain these to you, but I can’t – especially not the last one) to test a series of hypotheses that are neatly summarized by the author in this one sentence:

“Users who generate the most message replies, comments, or conversations, or spread the most word choices [aka online leaders, the dependent variable - MV's note] were expected to exhibit more communication activity and tenure in the community, more network centrality and brokering behaviors, and language that exhibits talkativeness, affect, assertiveness, and linguistic diversity [measures of the independent variables, MV's note].”

After testing relationships between these variables, the following emerged as characteristics of online leaders:

Online leaders:

1. post a lot of messages and a lot of replies (high communication volume)
2. have been part of the group for a long time (online tenure)
3. engage with several different members of the group
4. engage in back-and-forth dialog with members of the group
5. tend to write longer messages than other group members
6. use a richer vocabulary that other community members. Tthis is linked in the research literature to cognitive complexity – i.e. how smart one is – and therefore, to credibility. Or, it is possible that the richer, more colorful language draws readers in.
7. are assertive
8. express affect and emotion (attitudes) – which, along with assertiveness, may be an indicator of leaders’ passion for the topic
9. are able, through behaviors 3 and 4 above, to create supportive, loyal relationships with other community members and between them. Leaders are important to the success of the group as a whole because they are instrumental in creating and maintaining relationships within the community.

The only characteristics that was not associated with leadership was brokerage.

Of course, these findings are valid for discussion groups. We don’t know yet if they apply to other types of online communities.

So, what do you think? Do these sound to you as reasonable characteristics of online leaders? Will this study change the way you identify online influencers?

New Pew report on social media use

PIP_Twitter_Fall_2009 –

Research Study: @sockington is more influential than @chrisbrogan

This Webecology research report has been making the rounds on Twitter. I haven’t had time to read it until now, here are my reading notes:

The Webecology team uses large scale data mining to identify patterns indicative of online culture and community. Wish I’d do this, too – and will, as soon as I find a research partner to help with the data mining part.

For this project, the authors set out to create a more accurate measure of influence on Twitter that goes beyond either:

1. number of followers; or
2. followers/friends ratio

The authors defined influence on Twitter as:

influence on Twitter = the potential of an action of a user to initiate a further action by another user

Specifically, influence means the potential of a tweet to generate replies, mentions (conversational behaviors), RTs, and attributions (content-pushing behaviors).

This is an atheoretical, operational definition of influence (the study’s Achille’s heel).

As far as I understand, all 4 actions were weighed equally. So, a RT factors the same as an @reply in determining influence.

They selected 12 Twitter accounts to study. The selection was based on this criterion: the 12 accounts were  ”widely perceived to be among the more influential users on Twitter.” It is not clear who did the perceiving, and what definition or measure of influence they used in the process of perception. IMO, the arbitrary selection of the sample is another major weakness – but in this case, I can live with it, because the purpose is not to derive conclusions about Twitter culture as much as it is to demonstrate how the methodology can be used.

Then, the 12 users were grouped into 3 categories. Here is a table with the accounts they analyzed, and their number of tweets over 10 days, as well as the number of followers and friends at the end of the 10 days:

—

Celebrities	Username	Tweets	Followers	Followees
Ashton Kutcher	aplusk	3,205	3,407,385	209
Shaquille O’Neil	THE_REAL_SHAQ	2,072	2,092,541	562
Stanley Kirk Burrell	MCHammer	6,016	1,331,797	31,202
Sockington	sockington	5,711	1,089,984	380
Justine Ezarik	ijustine	7,718	605,441	3,039
News Outlets	Username	Tweets	Followers	Followees
CNN Breaking News	cnnbrk	1,096	2,712,530	18
BarackObama.com	BarackObama	330	2,018,016	761,851
Mashable.com	mashable	17,914	1,363,510	1,925
CNN	cnn	11,607	193,625	50
Social Media Analysts	Username	Tweets	Followers	Followees
Gary Vaynerchuk	garyvee	7,532	862,790	9,683
Chris Brogan	chrisbrogan	48,341	94,715	88,431
Robert Scoble	Scobleizer	23,112	94,295	2,423

The data that they mined was as collected over 10 days, in August 2009. The data included:

• The 2143 tweets generated by the 12 users
• The 90,130 actions (responses, RTs) triggered by the original 2143 tweets
• All the tweets generated in connection with the 12 users (by their followers and friends;a total of 134, 654 tweets, 15,866,629 followers, and 899,773 friends/followees)

The authors produced 2 types of influence reports, based on the type of action that was triggered:

1. conversational action (people replied, or mentioned the user – e.g. “meeting @stockington for catnip”)
2. content-pushing action (people retweeted, or gave attribution – e.g. “via@username”)

Please note that a mention may or may not be a response to a tweet. If they were not responses to a tweet, they fall outside the authors’ definition of Twitter influence, and they should have been excluded from the analysis.

Here we go, on to the findings:

Conversational action

This graph shows you the amount of conversational activity (@replies and mentions) each user got in response to one (average) tweet.

Content action

This graph shows you how much content action (retweets and attributions) each user got for each (average) tweet:

So here we see that, per tweet, @sockington did get more retweets than @chrisbrogan.

The authors claim that these graphs of influence/tweet are the most accurate measure of Twitter influence so far. Therefore:

@sockington IS more influential on Twitter than @chrisbrogan,

because the fake cat gets more retweets. (sorry, @sockington, I do love you!!!)

I know exactly what you’re thinking, it starts with B and ends with T.

That’s because here we have a problem of construct validity. The measures do not actually measure influence. I wish the authors had read some research in communication & persuasion about the concept of influence, then worked their way from a conceptual to an operational definition.

Obviously, @sockington gets more retweets because he’s cuter & funnier than @chrisbrogan (sorry, Chris!). We don’t know why people reply or retweet. This study ignores a very important aspect of human relations: meaning. There is meaning in tweets, and meaning in why people retweet. But that is not captured in this study.

That being said, the report shows what can be done with data mining – it’s awesome! With a bit of help from people who know how to study meaning (hint, hint!), this type of research will be extremely valuable.

If anything, let this be an argument for computers & communication people working together, across disciplines.

In a future post, I will review conceptual and operational definitions of influence.

Dr. V breaks out of the ivory tower

It strikes me that I can write conference papers and journal articles – but they have no impact, because no one reads them. Even if people want to read them, they don’t have access, because most academic journals are protected behind walls, and the password costs hundreds, if not thousands, of $$$ a year.

But I wrote one white paper (the first one, because I’ve been trained not to believe in self-publishing: “If it’s not double-blind reviewed, it doesn’t matter!”) and I’m amazed to see that all of a sudden I get media attention – and most surprisingly, that PR and marketing practitioners out there are actually interested in theory and research!!! (what rock have I been hiding under?!).

Here are a couple of media pieces based on interviews I’ve given:

• an article in BtoB about online news releases
• a podcast interview about social media and some of my recent research (importance of blogs in PR, social media & culture, online news releases)

The ROI of online news releases study got more media coverage, you can find a list on Jiyan Wei’s blog, but I’m not sure if he updates it…

Oh, and while I’m at it, I wrote a book, too, I guess that should count here, though the price and academic writing style might keep it in the ivory tower…

I’m thrilled to at least open a window of the ivory tower, which I find so suffocating!

Blogs matter

Thanks to all of you who participated in my survey about the importance of blogs in public relations!

Here is my presentation of the results (runs about 19 minutes).

If you quote this presentation, you can use the following citation:

Vorvoreanu, M. (2008). Blogs matter. Panel presentation at the National Communication Association Annual Convention, Public Relations Division, San Diego, CA.

Here are some highlights from the results, based on a convenience/viral (non-probability*) sample of 203 respondents:

Blogs matter in hiring decisions

• Among respondents with 5+ years of experience in PR, if they had a choice between equally qualified job candidates, but one candidate had a blog and the other one did not,
  • 74% would hire the one with the blog
  • 19% would hire the one without the blog

• Both people who blog and do not blog are more likely to hire the candidate who has a well-written, good professional blog. Among the respondents who do not write a blog themselves:
  • 57% would hire the candidate with a blog
  • 33% would hire the candidate without a blog

• Respondents who write a blog:
  • 86% would hire the candidate with a blog
  • 8% would hire the candidate without a blog

Blogs matter for individuals

I asked PR bloggers what benefits they have derived from blogging. These were the most frequently mentioned benefits:

1. Contacts, networking, engaging with PR community (26; 34%)
2. Business benefits: jobs, clients, income, internships, speaking opportunities (21; 27%)
2. Learning, keeping current (21; 27%)
2. Gaining recognition, credibility; thought leadership; personal branding (21; 27%)
Other: Sharing knowledge (10; 13%), SEO (6; 8%)
None: 3; 3.9%

Blogs matter for the PR profession

I asked both bloggers and non bloggers how they thought PR practitioners’ blogs impact the PR field.

• 91% of respondents said PR practitioner blogs have a positive impact
• 6% said PR practitioner blogs have no or very little impact
• 2% said PR practitioner blogs negative impact

PR practitioner blogs increase practitioner knowledge and move PR towards higher standards of professionalism

• Knowledge benefits (75%):
  • Educate each other (23%)
  • Create & share knowledge & best practices (32%)
  • Dialogue & discussion (17%)
  • Unify PR field (10%)
  • Keep current (6%)
• Professionalism benefits (18%)
  • Increase transparency; flack (9%)
  • Higher professional standards (6%)
  • Prove the value of PR (3%)

I encourage you to view the presentation so you can get more details and put these findings in context.

*Please remember that this sample is not representative of PR practitioners in the U.S. – or we don’t know if it is – so we can’t assume that these results apply to other people who did not participate in this survey.

Thanks again to all who participated and let me know if you have any questions!

Do blogs matter in PR? I need your help with new research project…

I’ve started a new research project about the importance of blogs for PR people & the industry as a whole.

I’ve got a favor to ask you: Would you give me 7-8 minutes to take this online survey?

If you’re a PR pro, student, educator, whether you blog or not, I need your thoughts.

I’ll share the results in academic papers and presentations, my PR Connections blog, and here.

Thank you, thank you, thank you!

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