Sunday, April 17, 2011

The Dirty Underbelly of Foursquare (Session 7)

Part 1: Official Rules

The SNS I am examining: Foursquare

Foursquare is a geo-social network that is accessed through a smartphone. A user dashboard is also found on the web. The link above lists the "house rules" for foursquare. This page is not accessible via the iPhone app though a savvy user could point their mobile web browser towards it. Personally I find this to be a bit problematic as nearly 100% of the time users access the SNS it is done via the smartphone app.

The house rules go through all of the DOs and DON'Ts of Foursquare. The DOs are helpful for people seeking questions about the basic use of the site like finding friends, checking in and leaving tips. The DON'Ts are basically a quick summery of the policies. In summery the five DON'Ts are:

          1)   Don’t check in when you’re not at a place

I imagine that many people break this rule but it would be difficult to find any data to really know for sure. The location in Honolulu with the most check-ins is the airport (HNL). The user who holds the mayorship (most check-ins) has checked in 47 times. This seems high for an airport so my guess is that this user works at the airport or is checking-in without actually being there. However, either way there is no real value gained by being the mayor of the airport so it might be an accurate check-in count according to Foursquare rules. Needless to say, this would be an extremely difficult rule for the Foursquare team to monitor and enforce.

          2)   Don’t create venues that do not exist

It is much easier to find data concerning this DON’T as all venues on Foursquare are searchable. The rules state specifically not to post locations such as “stuck in traffic” yet in Honolulu alone there are 34 different locations that violate this rule.

 I also found a place in downtown where you can check into outer space. (Disclamer: Outer Space does exist but not on earth. This might also be a real venue I just don't know about).

          3)   Don’t check into someone else’s home if you’re not there

This rule goes on to say, “Home venues are sensitive and it can creep people out to see non-friends checking in.” On Foursquare home venues are encouraged but to help with privacy they do not show up through a location-based search. Instead guests would need to search for home venues by title. I agree with this rule but am unsure how foursquare is enforcing/monitoring it. There are few (if any) options to report/block a user who are checking into people’s homes.  

          4)   Don’t leave tips with inappropriate language or negativity directed at another user.

[Warning: Explicit Language Below]

This is straightforward. Yet, what constitutes “inappropriate language” is always debatable.

I'm not really sure what to make of this tip:

          5)   Don’t spam via tips.

It always bothers me when I see tips suggesting people to try a different venue for a better product. I always assume these are written by the competition. (I see this more on Yelp then on Foursquare). After doing some quick searches on Foursquare I was unable to find tips that looked like spam. Venues will sometimes add their own tips in an effort to promote their product. I am not a fan of this either but there are no rules against it.

Part 2: Interpersonal Conflict

Interpersonal conflict is difficult to find on Foursquare. There is very little “chatting” that happens on this SNS. I also was unable to find any evidence of any official actions or warnings happening.

Below are a couple of tips left on Foursquare that lie outside of the way this SNS’s intended use.

And my all time favorite (More funny to me then anything else):

Part 3: Taking Action

One of the things that attracted me to Foursquare was that the features can be used in several different ways. Gazan [2009] states, “In a Web 2.0 environment, there are often multiple communities operating simultaneously within the same site, at different levels.” With this being the case on Foursquare, I imagine it would be difficult to manage all levels equally. If the purpose of using the site is to keep a digital record of places a user has been then the content in the tips might be of little importance. If, on the other hand, the user wants to know more about a venue then tips that contain little or no “chat” would be useful. However, if users want to communicate with other users than more “chat” in the tips would be what they are looking for. Regulating this so all the different levels work and benefit each other would be difficult. Gazan [2009] goes on to make the point that users continually reshape the communities and that the designers cannot plan how the reshaping happens but that they can be ready when it happens. It seems for this to be effective designers would need to keep a close eye on how features are being used on the SNS.

As a user of Foursquare my biggest complaint is that sometimes I cannot find a venue or a venue is being called something other then what I know it by. A more rare problem is that sometimes a venue is listed more then once. Both of these issues are solved through member-generated input. Using this method has its pluses and minuses. As Cosley et al. states concerning member maintained communities, “Some people will do a poor job, while others may deliberately sabotage the community.” Members can always create unlisted venues but this would require an active member to actually go in and do it on the SNS.

Kollock and Smith state, “The temptation is to enjoy a public good without contributing to its production, but if all reach this decision, the good is never created and all suffer.” This is an interesting statement when looking at it through the lens of Foursquare. Very little activity happens on Foursquare as opposed to the larger SNSs. There is also very little interaction between users outside of following social patterns. Looking back at the check-ins at HNL, there are a total of 24,123 by 11,356 different users. This venue has 89 tips. Some users have left multiple tips but the list cannot be organized by user so it’s difficult to know exactly how many are repeat tippers. With all this being said only 1 in every 128 users are leaving tips. This is less then 1% of the users communicating in ways other then simply checking in. To put this another way, less then 1% of the Foursquare community is contributing while the over +99% is benefiting. (A more in depth analysis would need to be done to get more accurate numbers).

This leaves a lot of room for unintended use to take control. The “Patriotic Nigras” example by Dibbell is interesting in the sense that these websites seem very vulnerable when interactive use is so low. It would be easy for rouge users to punk the system and when this happens the very large number of casual users will become annoyed and loose trust in the system.

If I were a systems administrator for Foursquare I would want to make sure there was a system set up for users to edit venue information by making it open source. Users then could clean up things like multiple venues or wrong venue names. As of right now all a user can do is flag a venue [See screen shot below].

 It would also be a good to add a “flag this tip” feature for inappropriate tips.

Foursquare has an option for some users to be come “supersusers” (SU). There are different ranks of these SUs. Depending on their rank they can edit venue information. As of right now Foursquare is not upgrading anyone to SU.

4: 5 Unwritten Rules

          1)   Only leave tips that will be of benefit to the largest undefined consensus of people. Inside jokes or day specific information is useless and might result in user distrust.

          2)   Only check into venues during operating hours.

          3)   Do not check into a venue if you are an employee. (This is actually a difficult rule because I think employees should check in so customers can know who is working but I think it would be more useful for Foursquare to develop a feature for employees specifically. One tab for who’s here and another for who’s working).

          4)   Do not leave tips that redirect users to another venue.

          5)   Do not create multiple pages for the same venue.

Sunday, April 3, 2011

Session 6: Online Identity and Interaction

I believe that the greatest invention in all of history is broadband technology. Broadband has given us the ability to communicate with each other in ways that less then 100 years ago was considered to be only possible by the divine.

Wellman stated, “Communication will be everywhere, but because it is independent of place, it will be situated nowhere.” Outside of the business world, I believe this statement to be 100% true. When I was a child and wanted to hang out with my friends I would call their house and hope that someone would receive the call so we can make plans and meet up. If I wanted to send my grandmother a birthday card I would send it to her home. Today, instead of communication being connected to a place it is connected to the person. I no longer call someone’s home but instead just call the person using mobile phone or wireless broadband technology.

I know this is not a new understanding of communication but as I was thinking through our current forms of sending and receiving information I began wondering about how little I (we) have embraced these abilities. Every cell phone comes equipped with voice mail but voice mail is a feature that was only needed when communication was restricted to a location and not a person. Voicemail was a need when people were away from their homes. Now that we call the person and not a location voicemail has become obsolete. What do we say in a voicemail that does not already get communicated through caller ID? Today, I am more likely to leave a voicemail with someone if I don’t want to receive a call back. A voicemail that says, “Just seeing what you are up to tonight give me a call back,” conveys no more information then a simple missed call notification.

Probably the most useless aspect of a voicemail is that it is a recorded audio message that allows for very little interaction. Take the above message example: In the amount of time it took me to call someone and leave that message I could have created either a Facebook message or a rarely used Google Wave and informed friends of plans including a list of who has committed to meeting up for the evening, real time location sharing of everyone’s current position, reviews and links to some possible destinations and a live feed of suggestions of activities.

Donath’s article speaks at length about social grooming and how that can be used to communicate with friends within the same network. Liu took this idea further and studied the personal impact and benefit of social grooming on MySpace. A huge dilemma within anthropological studies of online communities and SNSs concerns the true identity of one’s online self. When I was a freshman in college I found myself reflecting on my life and questioning if I influenced my environment or if my environment influenced me. Put another way, why do I find one form of art appealing while others remain uninteresting. The question concerns how much control we have over our subconscious. However, with our digital selves we are in 100% control over how we present this aspect of our lives.

When it comes to digital grooming and the disclosing of personal preferences we can choose to be as honest or as eccentric as we want to reveal. If my musical taste revolves around local independent bands but found myself really enjoying the latest Katy Perry single do I chose to disclose this information online and if I do or do not how does that impact the authenticity of my digital representation.

The authenticity of one’s digital self can impact recommender systems in both positive and negative ways. Liu stated, “The limitations of these large-scale computational and statistical methods include the loss of some transparency —not always being able to understand how a generalization was reached or how it can be mapped back onto specific examples; and the loss of some precision—not being able to model all the technical factors and data interactions that explain a conclusion.” For Liu on MySpace and now more on Facebook we digitally groom our profiles to portray us in a specific way. For these websites we chose to make public the experiences we want to share while hiding others we do not want people to know about. For a SNS like Facebook where most of our friends are people we know from offline experiences this is not that big of a deal. Yet for websites that incorporate a recommender system, such as Netflix, this becomes a much bigger issue. Once a film has been viewed it is connected to your profile and that information will need to be processed in some way for Netflix to make an accurate suggestion. Netflix employs a star ranking system so the user can communicate somewhat with the recommender algorithm.

Still there are some films that have troubled the Netflix recommender. Techdirt refers to this as the Napoleon Dynamite problem. Mike Masnick of techdirt states, “No one seems quite sure what leads to such a strong polar reaction, and no algorithm can yet figure out how people will react to such films, which is where all of the various algorithms seem to run into a dead end.” He goes on to note that placing too strong of an emphasis on algorithms and not enough on social filtering could have cause this issue.    

So when it comes to choosing the next movie to watch we can either trust the recommender systems to properly evaluate our digital profiles (do we have control of our environment?) or we can match our preferences up with our friends with similar taste (does our environment control us?)

Both Foursquare and Whrrl, both geosocial smartphone apps, just announced a recommender system that will help give suggestions based on past experiences and location. For these websites the digital grooming of ones profile is much more important if we care to receive accurate results. But at the same time there seems to be more quality in simply being able to compare Foursquare experiences within tightly knit social circles. Would we be more likely to try a restaurant if a friend tells us to or if our smartphones do? With smartphone apps like Blacktop entire vacations can be presented in a single screenshot including notes on all the various places visited. 

Would this be more useful then checking out a tour book from the library?

Or if I have a friend moving to Hawaii they can simply browse my Foursquare page and know all the best places to eat, get their hair cut and the best secret beaches to swim at. Now a general landscape of the city is much more easily accessible thanks to these geosocial tools.

So do people join Foursquare to play the geosocial game and to accrue mayorships (the social capitol of Foursquare) or is it more to leave a digital log of where they have been and to potentially meet up with friends? While the majority fall under the first category the second is actually where the benefit of these tools lie. Yet the problem with Foursqaure, or any geotagging SNS, is that it is only about where you have been and not so much about where you are going.

The future of proximity communication, and the beauty of wireless broadband technology, lies in real-time location sharing. The best smartphone apps I have found to accomplish this is Geoloqi and Google Latitude. While neither of these are SNSs in the traditional sense they can be quickly incorporated into any form of messaging including SMS, e-mail, Facebook and Twitter. With these apps you no longer need to tell people how far away you are but instead just simply send them a link to your map and they can track you the whole way. These tools can also help friends meet up at in large open spaces even if they did not know they were there together. For instance if two people were to check into Ala Moana Beach Park around the same time with Google Latitude the map will show them in close proximity of each other and would allow them to meet up.


The other day a friend of mine posted on Foursquare that he was in downtown Seattle for the afternoon and that he wanted to meet up with someone (anyone) for lunch. To help generate more contact with the Foursquare check-in he pushed it onto his Facebook wall.

This seems to be a common practice in Foursquare and might work if someone who was already downtown happened to see the Foursquare check-in. However, the limitation of Foursquare here is that the user can only check into one place at a time or continually check into places as he moved around the downtown area.

How this could have been resolved: Had he used a real-time location app like geoloqi he could have set it to update every 5 minutes allowing him to be seen by anyone who copied the link from his Facebook wall. By using this feature a friend who might be in the same building without otherwise knowing could then message him and possibly meet up for lunch.


Anyone who has attempted to ride a bicycle around the busy streets of Honolulu will know how unpredictable and dangerous a bike ride can be. Personally I have found that the best times to ride my bike is at night however finding others to join me at these hours is difficult. So if I am headed to meet up with someone I will send them a link to my current position using Geoloqi. As I am on my way to the destination they can check my current location either on a computer or a phone and know exactly how far away I am. Also if they notice that I have stopped moving they can see where I am at on the map. If I happen to be someplace that serves Manapua, for example, they can send me a geonote to put in an extra order. If I happen to be stopped in an unusual place then they can call to make sure I’m alright. If I happened to not answer the call they would still know my exact location.  


By using the explore feature on Foursquare I can see all the popular places right at this moment. This feature could be useful if I wanted to go to a popular restaurant but didn’t know which one. Most popular places will also have many useful tips letting the user know if it would be worthwhile to eat at this place. I can also limit the app so I only see where my friends have checked in. This can be useful if I am out and am looking for a place to grab a quick meal but do not really know what all my options are.

Saturday, March 12, 2011

1,000 Monkeys Sitting At 1,000 Typewriters...(Session 5)

As I was reading this sessions articles I could not help but be reminded of a one-act play I was in during college. The play is called Words, Words, Words by David Ives. In this performance I played a monkey named Milton whose character was loosely based on the personality and writings of John Milton. The other two monkeys were (Jonathan) Swift and (Franz) Kafka. The plot is structured around the infinite monkey theorem which suggests that, “a monkey hitting keys at random on a typewriter keyboard for an infinite amount of time will almost surely type a given text, such as the complete works of William Shakespeare.” (Quoted from Wikipedia)

The Wikipedia experiment nearly asks the same question but instead shifts the action onto the user. Wikipedia has an advantage as their “monkeys” have access to source material while the monkeys in the theory above are just randomly pushing buttons. The problem with both experiments is if close enough is sufficient.

Several of our readings addressed this “close enough” question. Leibenluft’s A Librarian’s Worst Nightmare article directly exposes Yahoo! Answers inaccuracy. Duguid’s article Limits of Self-Organization exposes inaccuracies in Gracenote, Project Gutenberg and Wikipedia. And Gazan’s article Social Annotations in Digital Library Collections exposed the trend for users of a FAQ website to submit more social answers as opposed to strictly factual answers.

Now before I go any further with this post I must stop and honestly ask if the general public would be more likely to read/buy The Complete Works of William Shakespeare if they knew it was produced by a monkey sitting at a typewriter or (and I honestly intend for this to be a completely separate question) would we be more likely to read/use a FAQ website or an online encyclopedia if we knew it was being written/created by our peers?

This session’s topic is the exact reason I chose to take this course and I found this session’s readings to be fascinating when I think about them through the lens of librarianship. I am tempted to write individual posts about all four of our prompts but will restrain myself and focus only on: Social Tagging vs. Professional Cataloging and Classification.

I first began thinking about Web 2.0 and Librarianship early last fall. I was curious about my current online practices and how these practices could be useful for OPACs. Around this same time I received an e-mail from the Seattle Public Library (SPL) announcing the release of their new catalog that would be full of Library 2.0 tools (social tagging, history tracking, following users, user generated lists, comments …). Specifically for this post I will focus on the use of social tagging in their OPAC and compare it to their traditional cataloging system.

Perhaps my favorite aspect of Library 2.0 tools is the fact that the user becomes engaged and an active participant in information retrieval (IR). What this means is that a portion of the catalog is reserved for those who have actually read or interacted with the resource. Catalogers, if we are honest with ourselves, do not read all the books they catalog but patrons do. This makes patrons more knowledgeable about the books in a collection then the catalogers so why not give them access to the cataloging process?

The activity on SPLs OPAC is best described by Haythornthwaite’s term “lightweight peer production." To contribute to the OPAC users do not need to make long-term commitments, they do not need to build social capital and they do not need to maintain or groom their contribution. Social tagging on SPL’s OPAC is as simple as clicking a link and entering the content.

This new aspect of SPL’s OPAC is utilizing an online concept that many (if not most) of their users are already using: Social Filtering. Kristina Lerman stated, “Rather than actively searching for new interesting context, or subscribing to a set of predefined topics, users can now put other people to task of finding and filtering information for them (2).” Due to Intellectual Freedom issues SPL’s OPAC works a bit differently then DIGG or Facebook where users are more or less open to full disclosure. Since libraries are a finite community (limited to only those with a library card) their collections are already being filtered concerning a particular slant (i.e. the community). So it may be safe to assume that social filtering in Library 2.0 enhanced OPACs are working the same way.

I am increasingly curious if social filtering would be more useful in academic/research OPACs and digital collections. Gazan stated, “While used textbooks are obviously less costly, they often carry another benefit new textbooks don’t: highlights, underscores and other annotations by their previous owners (1).” While thinking about this statement I began thinking about a new (perhaps?) concept that utilizes a common practice in social computing. That concept being Social Highlighting. Many of us already geotag ourselves when we are out by checking into restaurants, coffee shops and so on. What this is doing is cataloging our routines. Just this week both Foursquare and Whrrl have created an algorithm to compare users activities with their friends and with the greater community. To put this more popularly, on a SNS like Whrrl all of our digital selves are getting together and talking about what we have done then based on that digital discussion my digital self will come back to me and tell me what I should do next. What this is doing is taking our self-documenting digital selves and finding patterns within the larger community. Lorcan Dempsey calls this “A ‘signed’ network presence … People have become entry points on the network, and signature is important (13).”

Below is an example of a Whrrl suggestion:

If patterns in our daily lives can be recognized, which I believe they can, then digital representations can help promote productivity. Both Netflix and Amazon do this with amazing accuracy as they make suggestions based on what we have viewed. Think about the impact this could have on library OPACs. An app could be integrated into an OPAC that says, “students who have previous taken the courses you are enrolled in have viewed the following resources.” Digital Highlighting, as I introduced above, would work in a similar way. Now that digital resources can be digitally annotated those annotations can be preserved and should be viewable by future patrons. The digital catalog could create a map of previous annotations and even rank those annotations based on frequency. The question comes up as to if this would take away from the learning process and I would suggest no. Essentially, all it is doing is letting our digital representations get together for a conversation and based on that conversation making suggestions based on previous patterns.

One aspect silent in this entire conversation concerns the role of the library at a much larger scale. Libraries are collections of resources and not individual resources. Cataloging, in one sense, is collocation. Subject Headings allow for collections to be brought together in a way that is useful for its users. The controlled vocabulary works best at the collection level and not at the individual resource level. Library 2.0 works the other way around. Social tags are more about describing the work in hand then it is about figuring out where in the collection the book belongs.

In the SPL OPAC I found the following movies to be good examples of where Library 2.0 falls apart: Never Let Me Go and Casablanca. I noticed that one of the tags for the movie Never Let Me Go is “Bad Hair”.

 I question if this is a useful tag for this movie. As I have not seen this movie, it is possible that a character has to deal with a bad haircut but my guess is that whoever tagged this movie just did not like one of the character’s haircut. When I followed this tag I found that there are two movies with this tag and my guess is that the same patron created them. For Casablanca there are two tags that are the same concept but spelled differently: world war two and wwii. This makes me wonder if other resources about World War II would be hidden based on this duplication.

These tags are more or less creating taxonomy clouds. If the descriptions are vague or wrong then it makes the clouds less useful for future patrons. Adding a more useful help screen and then explaining what the goals of the program are would help this aspect of SPL’s OPAC. If collocation is important it should be stated.

I began this post by suggesting that patrons using Library 2.0 tools are similar to monkeys pushing buttons at a typewriter. But this would be stated better by suggesting that non-professionals or patrons can be helpful in the cataloging process. They can also be excellent resources when it comes to describing items in our catalogs. But I think more important is the way patrons are using resources, how that process is digitally cataloged and then socially filtered.        

Friday, March 4, 2011

Some Outside Reading/Final Project Opportunity

As if any of us need any outside reading but I found the following links to be super fascinating!

I'm also curious if anyone would be interested in joining me in doing some in-depth research on a new aspect of social media. It is called Cyborg Anthropology.

You can check out a website here:

A great article from the Portland Mercury

Also a couple of video's to watch:

I have been thinking a lot about how our digital selves communicate with our real selves as well as the impact of digital grooming.

To participate with me in this project you will need to have a smartphone and you will need to download the app: geoloqi

I know this is all really vague if you are interested or if you just want more information feel free to comment below.

Sunday, February 27, 2011

Is Web 2.0 Turning Us All Into Robots or: How I Learned To Swallow The Pill And Let The Web Follow My Every Step

I was intrigued by a statement at the very beginning of the Gleave et al article that stated, “Social life has moved online. From discussion boards, to wikis, to social networking sites, people do things together through digital communication. Those interactions leave behind complex records of who did what, when, under what context, and with whom. In other words, the interaction order is now electrified and self-documenting (1).”

This “self-documenting” environment that we now find ourselves in has many interesting facets and I have been slowing evaluating them to find out if I am a fan or not. The amount of peripheral knowledge we now have about ourselves is massive. For example I could tell you the exact time and date of the last 8,613 songs I have listened to in my digital music collection. I could even list them all in order from most resent, which was about 10 minutes ago, to the oldest, which was on August 1st 2009 at 5:18 pm. 

As our daily lives are being merged with electronic media a digital residue is being left behind. We must ask ourselves what we are going to do with all of this peripheral information about ourselves.

Websites like Amazon and Netflix have already shown how this can be useful information. Have you ever watched a movie or bought a CD because your computer told you too? I sure have. Netflix will say, “You have seen these movies and based on the viewing habits of the entire Netflix community you will probably like these other movies.” Amazon has a similar practice where they will auto suggest items for you to view based on what you have looked at and what other people have bought.

Facebook has the potential of working in a similar way. This is especially true of the way it was originally developed with finite communities. Ellison, Steinfield and Lampe stated, “Our participants overwhelmingly used Facebook to keep in touch with old friends and to maintain or intensify relationships characterized by some form of offline connection such as dormitory proximity or a shared class (1162).” For instance, joining a group on Facebook adds information to your profile that potentially make it more easy to be found. This happened more often on MySpace for me personally. Once I listed my High School and graduation year onto my profile I began to get friend requests from people I had not heard from in years.

But you all know this already! I’m not presenting any unique perspective that we don’t already encounter on a daily basis.

This week I chose to take this digital residue self-documenting idea a step further. I joined two SNSs that are specifically designed to let others (your friends or the general public) know where you are or where you have been. The two SNSs I used were Foursquare and Yelp. These are both SNSs that I only know about based on other people’s experience but have never used them myself. Both of these sites use geo-tagging to let people either know who is currently at a location or who has been there before. Though out the week I checked myself into as many places as I could remember to see if either my social interaction could be improved by logging where I have been or to see if I could find out information about the places I have been that I previously did not know. I also wanted to see if the social capitol gained in using these SNSs led to any better or different social interactions.

Both of these SNSs can interface with Twitter and Facebook and help me quickly find friends who use these sites. Yelp was much better at this then Foursquare. At the end of my first day of using Yelp I already had accumulated five friends (all people I know in real life) while after using Foursquare for a week I still have yet to gain any friends.

Both of these sites use badges to communicate my activity with other users. What this means is that the person who checks in the most at a particular location will either become the Duke (Yelp) or the Mayor (Foursquare). Once you achieve this rank your picture will be seen by anyone who checks into the location. Personally, I did not find this aspect to be the best part of these SNSs. The most useful feature is that on both of the websites users can leave tips based on their experience. This is where I was able to connect with users the most, though in a very static non-personal way.


These are both tips left concerning Hamilton library. Through some of the info seems humorous to those of us that might be in the library 2 or 3 times a week it would be useful information for those who might be visiting for the first time.

I particularly enjoyed the following screen concerning Hamilton Library which I found on Yelp:

This aspect of these SNSs got me thinking about the statement in Allen, Colombo and Whitaker that said, “Individuals restrict interaction to those with similar identity, periodically mutating their identity and copying the behaviors (neighbors and strategy) of those receiving higher payoffs. The result is that an incentive structure emerges where free-riders become isolated (2).” As a new user I did not feel compelled to become the next Duke/Mayor even though the site was encouraging me to do so.

You can see in the image on the left that I am 6 days away from becoming a Mayor.

Also, I was not all that interested in connecting with people who I did not already have an off line connection with. These sites could have become more dynamically layered if these two aspects were important to me. As a newcomer to the site I did not feel like I was at a distance for those who had been using the site for a while. I did not feel hindered or restricted in any way when adding new information to the sites.

Most people are familiar with Yelp as a review resource for things around town but adding a geo-tagging aspect to the site made it a much more interactive experience. With this being said, the beauty of using these two sites together was the way they interacted with each other’s strengths. My experience and opinion is that I would be more likely to choose a restaurant to eat at based on information on Yelp. I could then use Foursquare to figure out what specifically on that restaurant’s menu I would want to eat.

These SNSs are perfect examples of Williams’ statement, “Socializing online can never compensate for lost socializing offline…the online world is a site for social activity, both original and extended from offline life (596).” Neither of these sites would exsit without people wanting to log their offline life in an online format. It seems increasingly evident to me that my online status is 100% dependent to my off line activity. Having a way to keep track of what I have done in the past through an online means seems to have increasing potential. Though the trust issue is the hurdle we must get past. Never did I feel comfortable to check in to my own home but I did check into a public park after dark. When information is made public there is always a chance that it could be used in an unwanted way. There are probably things I do that I would not necessarily want or need everyone knowing (for example when I checked into Costco).

Gleave et al states, “As more of the social world becomes essentially self-documenting, social roles will increasingly be observable as a function of both social positions, as with early block modeling efforts, and content analysis and ethnographic methods (9).” The social capitol on both of the SNSs I joined this week are more or less defined by individual users. The models proposed by Ellison, Steinfield and Lampe carry over as most of the interaction takes place off line. As the self-documenting aspects of these websites leave behind information about ourselves and our friends, patters can emerge and information can be gleaned. I would be curious if the next step for these websites is to create an option to auto suggest places for us to visit. A button on Foursquare or Yelp that will suggest a place for me to eat based on my past experiences and reviews plus my current location could create accurate suggestions.

Both of these SNSs could be improved by incorporating either more social capital by making it easier for  newcomers to gain badges or by diversifying the badges. Below are the first badges I earned on the respective sites.


I was particularly surprised when I checked into the library four times in four days and did not receive a badge for it. 

The sites would also be more enjoyable if more of my friends on Oahu were connected with me. I can see where all of my friends have checked in but when they are all in Seattle it does not do much good for me while I am here on Oahu.

I titled this blog is web 2.0 turning us all into robots because as we are self-documenting information more potential is created to find things we may enjoy. We can also quickly communicate with friends what we have been up to. Yet with all this being said I must ask if we really want our computers understanding our sub-conscience better then we ourselves do.

Final Project Idea:

I have been wanting to look into the potential of social tagging on library OPACs. Could user generated lists based on particular communities (i.e. a college course) help students find highly relevant resources? What would the role of librarians be in helping to maintaining the quality of these lists and social tags?

Update (3/1):

Another project idea: I would like to explore the impact/potential of the externalization of our personalities and the humanization of technology. What I would like to look at is the interaction between the real self and digital self and how the two communicate with each other and other's real/digital selves. This study would include looking into geo-note taking and real time location sharing and how our digital selves and communicate with each other and inform us of what friends in our proximity are doing as well as recalling past experiences that are location specific. I know this is a super abstract idea so I am looking forward to some dialogue. My inspiration:

Sunday, February 13, 2011

In Search of the 'Green Weenie'

Half of the top ten websites visited daily rely on user generated content. Of these five websites none of them pay their users for their posts. So why do people keep coming back? What is the attraction? And what is in it for the user?

These are the basic questions being asked in all five articles we read this week. Java et al stated, “Microblogging fulfills a need for an even faster mode of communication. By encouraging shorter posts, it lowers users’ requirement of time and thought investment for content generation (2).” In this article, Twitter specifically was found to be a quick and useful way to communicate. Ridings and Gefen looked into why people join online communities and found that membership is retained for two reasons: 1) to gain a feeling of affiliation or belonging, and 2) to gain information and to “aid in goal achievement (14).” They state, “Virtual communities, like real ones, are joined not only because of utilitarian information exchange, but also because they serve the social need of having a friend and getting social support (15).” For Ling et al user generated material is motivated by an idea of a collective contribution. Tedjamulia et al looks at how website designers can promote retention by rewarding the user. Through these various types of rewards users are given incentives to continually collaborate on the site. Schrock aproched the issue from the perspective of gender and states that “males use SNSs to meet new people and expand their friend network (for example, for dating), while females use them for maintaining existing networks (9).”

I must now ask myself if I find myself within the findings of these studies. Of the ten websites mentioned above I use 6 of them regularly, the 5 sites that rely on user generated material plus Google, contributing content to 3 of these sites. I have minimally added information to Wikipedia but not enough to call myself a contributor. Personally, I use blogger to communicate my thoughts and ideas to others, twitter to get information from others and Facebook more as a many-to-many form of communication. 

In general I have a hard time disagreeing with academic articles. Maybe this is a fault of mine but I tend to think, “If it’s published it must be true.” Yet, with this being said, I struggled to agree with Ling et al’s article Using Social Psychology to Motivate Contributions to Online Communities. I struggled through this article because I never really understood what they were analyzing. I understood the basic premise behind the study and the website they were using but this study mostly seemed like they were encouraging the users to simply push buttons. I think that one thing that would have helped support their results was to list the movies the users were voting on and expressed if the users were required to have seen the film. On the Internet Movie Database (IMDb), through I’m sure a much larger collection of movies then MovieLens, if you were to click on the “rate movies” and limit it to the movies with the least number of votes you would find that nearly 100% of the films listed are movies no has/will ever see because they are either projects from film schools or super low budget independent films that never gained national distribution (among other reasons). Ling et al stated, “More than 20% of the movies listed in the system have so few ratings that the recommender algorithms cannot make accurate predictions about whether subscribers will like them (2).” This study would have been helped with a statement that explained why these films were not rated.

Yet the ultimate question is if we can move past this annoyance to find meaning in the results of the test. The outcome of their study does, in a way, mirror my online behavior. The beauty of Web 2.0 is the ability to collaborate with other users. Nearly 100% of all of my contributions on the web are not for my particular benefit but instead because of the ability to use information collaboratively with others. This works differently on various webpages. Relating this back to MovieLens, or even IMDb, leaving feedback about movies is to inform or influence other users. This parallels the idea that users contributed more when given a group goal (Ling, 23).

To take this a step further Ling et al asked if the information users post needs to be unique. According to their study it does. I wonder if this is really true. I believe that once again it depends on the website being used. If this was really true would Facebook have developed a “repost” button allowing users to repost links and photos contributed by others? Or what about the use of hashtags on Twitter? How unique are the comments when a hashtag is followed? Sometimes each post is unique but many times all the posts tend to be similar (non-unique) to each other or simply reposts of the original statement.

On the other hand, both Ling et al and Tedjamulia et al discuss the importance of rewards as motivators for online contribution. I like to think of this as the MySpace phenomena. The mantra would go something like: S/he with the most posts on a fairly unknown bands page is the biggest fan. Facebook does not really have a devise for this and my experience has been that the person with the strongest presents on my Facebook wall usually posts the most meaningless status updates. Yet rewards are a useful tool on some websites. Geosocial networking sites, such as, work entirely on this principle. Badges are given for various tasks and the more badges you have the more you can brag about them. Tedjamulia et al state, “Non-monetary rewards like social recognition can be extremely powerful incentives so long as they are public, infrequent, credible, and culturally meaningful (8).” While it tends to contradict this quote, most of the badges on Foursquare tend to be arbitrary. By this I mean they could create a badge for almost anything and people would try to achieve it.

Personally, this reward system does not work for me. It is too arbitrary of a system and rewards people with heavy use without any way of evaluating the quality of the contribution. Instead the rewards that work better for me are recognition and praise. This is always generated by other users and not by mechanisms created by the designers.

A different form of reward I have recently found is national, or popular, recognition. Imagine if your contribution had the possibility to be made public on a network news show, would your contributions become more meaningful? Would you be more willing to come back and contribute more, less or the same? To help explain this theory, and to interact with the weeks readings, I will use Rachel Maddow’s blog properly called The Maddow Blog. This blog is maintained by the staff of the Rachel Maddow Show and is used as a way to diolouge and interact with viewers. It is also a way for the show to connect the viewers with important links and content from the show. The blog is hosted on MSNBC’s website and the comments on the blog are run through MSNBC’s social news website newsvine.

On the February 7th show, during a segment called "Debunktion Junction", Rachel Maddow made reference to a comment made by former Senator Alan Simpson. That comment being, “Stick your finger down your throat and give them the green weenie.” The question Rachel looked into was what Simpson meant by the term “green weenie”.

The answers that Rachel received came pouring over the social media she uses (her blog and her various twitter accounts). Now I love Rachel Maddow but sometimes she focuses on the strangest issues, and this is a good example of that. However, one thing this story shows is how she was able to use her social media to get some quick answers to these questions.

The next day, Feb. 8th, Rachel reported on this story more in-depth and showed how she was able to find the information she was looking for using social media and the help of some librarians.

It is difficult to match the timeline of the blog with the timeline of the show, especially since we do not know when the staff last checked the blog before Rachel went on the air but for some of those who posted information quick enough their posts made it onto national television.

After seeing that Rachel was quoting posts from her blog in her show I went back to the blog to examine the overall quality of the posts and to see how they support what I have been reading this week. Her blog that correlates with this story is called Tracking Down the 'Green Weenie' and was posted on Feb. 8th between the two shows. The idea here is that if posting on Rachel’s blog helps contribute to her show and also brings 15 seconds of fame to the writers of the comment then a majority of the comments should be of a high quality. I organized a majority of the posts into 5 categories that are listed below with the amount of times they occur:

1)   Information without a link (10)
2)   Information with a link (9)
3)   Commentary (9)
4)   Note to Rachel (8)
5)   No Information – No Commentary (7)

It was no surprise to me that nearly half of the post were presenting information is some manner. The quality of the information varied and often topics and links were repeated. The group I have called No Information – No Commentary were statements that did not add to the conversation:

Surprisingly Kaija has commented prolifically on the Maddow Blog many of which hold a lot more meaning then the comment above portrays. 

The group that surprised me the most were the notes to Rachel. To qualify for this group the posts needed to be addressed “to Rachel”. These surprised me because they were written as if they expected Rachel Maddow to read them and personally respond.

For the most part the comments that presented information concerning the 'Green Weenie' were substantive and often contained a link to further information.

The interface of the blog itself was very user friendly. If you look on the screen shot above you can see that you can quickly navigate to the users newsvine page by clicking their name in the upper left. You can also reply directly to the individual comments using the reply link on the bottom right. On some of the posts, next to the reply button is some text that says "1 vote". I have yet to figure out what this means and how the "voting" system is used on this blog. There is no feature on this blog to flag comments. All the blog posts on the Maddow Blog are posted by the staff of the show.

What I found on the Maddow Blog fell in line with Tedjamulia et al’s Proposition 5: “As ease of use and interesting content increase, more individuals will want to participate and contribute” and Proposition 10: “Participants with high commitment to achieving a goal will likely work harder to achieve the goal than individuals with low commitment”. The rewards for this particular blog post were two fold, first an informative blog helped to increase understanding of the ‘Green Weenie’ and second, there was a possibility of gaining recognition on the air during the show. Also, by recognizing that she values the contributions on her blog, Rachel reinforced informative responses.

I’ll be honest, before I began reading through the responses on her blog I was sure I was going to find some heated debates and Maddow bashing, which seems to be the norm these days. However, what I found was very little of that sort of rhetoric. There was little evidence of interaction or recognition between users on the blog which surprised me as well.