A7UmbrellaProject

A7UmbrellaProject

To-Do

Please Document the Following Sections:

• title for your course project
• members of your team
• abstract
• expected final outcome
• brief description of work done so far on the project
• brief description of work to be done in the next few weeks (e.g.: before spring break)
• describe specific research emphasis of every member of your team
• list of relevant references investigated
• list any specific problems you have encountered and need feedback/guidance on

GerhardComments

• you should collaborate, exchange information and notes with the "Participation Spectrum" project
• within your Umbrella project you should

• argue what defines the "umbrella"
• similarities and differences between your subprojects

• for the classroom analysis: you can compare the differences between the "game" course and our course
• some relevant references about motivation which you may take a look:

• Benkler, Y. (2006) The Wealth of Networks: How Social Production Transforms Markets and Freedom, Yale University Press, New Haven.
• Hidi, S., & Renninger, K. A. (2006) "The Four-Phase Model of Interest Development," Educational Psychologist, 41(2),
• Csikszentmihalyi, M. (1996) Creativity - Flow and the Psychology of Discovery and Invention, HarperCollins Publishers, New York, NY.

• you may want to differentiate your analysis between social networking environments (such as Facebook: focus is on communication, not on artifact creation) versus information repositories of artifacts (such as SketchUp or your Story Environment);
• you may want to differentiate your analysis between collaborative construction of one artifact (e.g.: Story Environment) versus aggregates of mostly individually constructed artifacts (e.g.: SketchUp)

Members

Kyuhan Koh, Jane Meyers, Jeff Hoehl, Catharine Starbird, Antonio González, Olga Liskin, George McCabe, Walter Mahfuz, Mikel King

Title

Umbrella Project: Motivations

Abstract

The main goal of our project is to gain a better understanding of what motivates people to actively participate both in online, social networking environments and in the classroom. In the social networking environment we define "active" as either the creation of new content, the reuse of existing content, or a response to existing content. Within the classroom, "active" participation is defined as the sharing and reuse of existing work. Although these projects are quite different our goal is to study these environments in parallel analyze them with similar techniques, and draw conclusions that universal to motivation and also those distinct to the individual domains.

A significant overlap across three projects will be determining systems to analyze the flow of contributions. In the social networking environment, these contributions will build on each other, creating an artifact or a series of artifacts. In the class programming and SketchUp environments, each student has the ability to see the contributions of other students and to borrow and reuse their code. In all three environments there is a flow of knowledge and creation. We will have to develop a mechanism or mechanisms to locate and analyze this creativity flow.

ExpectedOutcome

We expect to uncover and better understand many of the factors that motivate people to participate inside and outside the classroom so that they can be used to encourage more people to become involved in online groups. Examining the trends of participation can provide insight into why we actively contribute to a cooperative environment, whether or not we are consciously aware of these factors.

Through research in the Facebook domain, we hope to determine individuals' motivations to contribute to short stories. By analyzing statistics about contributors' behavior, we will be able to analyze key factors that motivate users to contribute. We expect to find a contributor's level of anonymity to be a key factor in influencing how and why people contribute. For instance, we predict that the more anonymous a user is, the less likely they will be to contribute valuable content wherein less anonymous users will produce work of a higher quality (i.e. more coherent, more serious, less profane). We also expect to find reasons why contributor's return to a particular story. We currently believe that repeated contributions to a particular story help to build an online identity and persona of a user. With repeated contributions to one piece of content, a user becomes a larger stakeholder of the story, has more control, and thus has a greater ability to reveal their persona (at the cost of leaving other contributors out). Similarly, we believe contributing to several stories not only helps to strengthen an online identity but also helps to create a sense of belonging to the story-creating community at large. In this regard, we also believe that we will find connections between the quality and amount of contributions based on the cognitive distance the user is from the community itself. For example, we predict that users contributing directly through the story-creating portal (i.e. the website itself) will produce higher quality and more frequent story updates. Conversely, we believe that users using the Facebook application will produce fewer and lower quality submissions. We believe a sense of belonging to the community will also influence the contribution styles of newer and older members. New members are predicted to contribute large amount often. As members become more senior, we believe their contributions will become less substantial in quantity but will continue to contribute over long periods of time and will contribute higher quality content.

Several points of analysis will also occur with outcomes we are unsure of and have no strong reason to believe will sway one way or another. We believe that stories with more attractive and friendlier titles will be completed faster. However, it is unpredicted to whether this will lead to higher or lower quality stories than those completed over longer periods of time. Similarly, we believe that stories with a lower maximum word length will result in drastically different contributions than stories with higher maximum word lengths. This difference between the two types of stories is also unpredicted. We have also already observed behavior wherein individuals will consistently repeat the same word or phrases in a likely attempt to create an online identity but the general effect of this behavior is unknown. For instance, users will consistently repeat the word "spatula" and "llama" across story contributions but the wide effect of this is generally unknown and unpredicted.

With regard to the code-sharing and Sketch-Up projects, our predictions generally align well with the story-creating piece. We believe contributions will be frequent and often for newer members but of higher quality and less frequency for more senior members. Similarly, we believe contributions will be largely centered on identity building and community membership and approval. Unlike the story-creating domain, we believe that competition will be a large influence on the code-sharing and Sketch-Up domains. A large motivation factor will likely be viewing and improving upon contributions made by other community members. Since contributions can largely be "owned" by an individual, there exists more motivation to produce higher quality work individually thus resulting in more competition amongst individuals. This contrasts with the story-creation wherein each story is "owned" by the community, not an individual.

In the Sketchup domain, we have formed four main hypotheses that we hope to prove. The first hypotheses is that altruism does not exist in a collaborative design environment. In other words, no user "selflessly" contributes to a design. This means that design environments should always provide a mechanism to "reward" its users. "rewards" may have a variety of meanings such as complements from others or even actual money. Whether or not altruism does not exist will be very hard to prove. However, we expect to find that most contributions stem from certain desires and motivations. We will break down the variety of desires and motivations in order to prove that most contributions stem from some kind of "selfishness." This will help us establish a better understanding of why people contribute. In the end, we hope to find concrete evidence that increasing "rewards" has a direct correlation with the amount of contribution a user makes.

The second hypothesis with regards to Sketchup has to do with competition. We believe that competition fuels contributions. When competitions are put in place, we believe that contributions from individuals and communities increase. We expect to be able to dissect the various reasons users participate in competitions. Also through analysis of various competitions, we expect to find what makes certain competitions more enticing than others.

The third hypothesis in the Sketchup domain is that the "richness" of a Sketchup community motivates members to contribute. We have broken down "richness" as communication (such as forums, tutorials, wikis etc.), size, and goals. We expect to find that communities with these components are the most successful communities and that these communities have a higher level of activity.

The fourth hypothesis in the sketchup domain is that the technological support system for a community is directly related to the amount of user motivation. Technological support systems provide different methods of communication between users. This communication can be broadcast or bidirectional. By comparing different technological support systems of different communities (tutorials, knowledge bases, Wikis etc.) , we expect to find which systems are the most effective. In the end, we hope to conclude that the communities with more versatile technological support systems are better at motivating their users.

WorkSoFar

Facebook Piece
=> Facebook was eventually chosen as our application domain for analyzing motivations to contribute to collaborative stories because of its extensive user base and its existing API. Instead of seeding with "word of mouth" methods such as notes we decided to look into applications because these environments provide more access to user data without the boundaries supported by public and private profile settings. While reviewing existing applications we found Story Gaps, an existing and popular Facebook application which provides all of the functionality we were hoping to integrate into our own system. This application not only has an extensive number of monthly users but provides public access to all stories ever created, including detailed information about who, when, and what was contributed as each piece of every story. Story Gaps is not only accessible through Facebook but also through a typical community website portal targeting individuals interested in collaborative story creation. Fortunately all users can interact with each other regardless of where they enter from and we can identify where each user has originated with their user name.

Recently we have been able to scrape of of the data from the StoryGaps website including information specific to each story, contribution, and user. This data has been coded using a data visualization and coding tool called e-dataviewer, which was modified to suite our data set. As we have coded, we found cause to make many modifications to our original coding scheme and have iterated several times since. The preliminary data analysis results seem to reveal some startling differences in stories created before and after integration with Facebook. In addition, we have recognized that users seem to take on one of these defined roles within their contributions on StoryGaps.

• "mischievous" - a contribution that changes a story, but with some sense of humor or creativity, either making a joke, repeating a word/phrase from the Storygaps culture, or creatively pushing the story in a new direction.
• "destructive" - a contribution that changes a story, takes it off topic or just adds jibberish, w/o being funny, creative, etc.
• "cooperative" - a contribution that fits either the story theme or the current theme
• "fixer" - someone who actively tries to bring a story back  to making sense, fitting an earlier thread, fitting the original theme, etc.

Other themes that have surfaced in our data analysis include small groups of people "taking turns" contributing to each others stories. Turn-taking behavior seems to be a behavioral reaction that has resulted from the story creation rules and a mechanism by which very small groups of users can monopolize and effectively "own" a particular story. We are hoping to explore this in more detail to determine whether this helps or hinders story coherency.

Code-Sharing
=>Since the last progressive report, we have finished building database to store up all features to capture course participants' activities. Also, we started writing a code to visualize the collected data. It will show how the complexity of game grows with the influence or inspiration from other classmates. We have surveyed with around 20 class students. This survey shows how actively they are engaged in the class, how often they are inspired by other classmates, how they collaborate with other students and so on. Some survey results are a little bit different from what we expected. It seems that we have to observe this experiment more carefully.

Sketch-Up
=>So far, we have installed and tested the Google Sketch-Up application and explored the Google 3D Warehouse. We have found out how to create models in Google Sketch-Up and have created two models for testing purposes. We have shared these models in the Google 3D Warehouse and explored how easily they can be found and edited. If the model's name is known, it is very easy to find a model via the search function. The problem is that, if the model is not featured or popular (which is only a very small amount of models that stick to various constraints), it cannot be easily found by just browsing the 3D Warehouse. On the other hand we have found out, that authors of models can be addressed directly and that there even exists the possibility to ask active community members to help with models. We considered this as an option to distribute our models. Another option we have discovered is the inclusion of popular related models into a collection that is maintained by us. People who visit these models can see the collections that contain this model and look at the other model in this collection, which would be a way to discover our models by browsing. Further, we have explored how the collaboration on a model works. A model can be shared publicly and made editable for everybody. If somebody wants to edit a model, he/she can select "edit" which will load the model into his/her Sketch-Up environment. After the changes have been made, the model can be uploaded and will contain the changes. (If the model is just downloaded without using the "edit" function, a new model will be created which enables branching.) Google provides a History, which shows who has contributed when and what changes he has done. A rollback function exists which can undo these changes. Further, there exists the option of "moderated editing", which means that the moderator will be informed about the changes and will accept or decline a change. This provides a certain comfort in tracking changes that have been made but might frighten off contributors. Another interesting option is that a Google Group can be attached to each model which allows discussion about the model and the creation of a small sub-community. That being said, up to this point we had more luck finding forms of contributions and less finding data to scientifically back up our hypothesis. Hence, our focus has shifted to an approach that is likely to examine motivation by what is provided in forums/groups rather than relying solely on the histories of the models. Nevertheless, we assume that the data that is not available now will be in the future, so some of our earlier framework is still being incorporated.

WorkToBeDone

Team as a whole
As a team, our plan is to bring our individual project findings together to create both generalizable and domain specific results about motivating factors for contribution.

Facebook
During the next few weeks, we plan to finish up data analysis concentrating our efforts on 3 distinct time frames in life of Storygaps, when first introduced as a website, when introduced to Facebook, and upon full adoption on Facebook. We also plan to create several interesting data visualizations that convey our findings. User demographic data of Facebook users will also be collected and analyzed where publicly available.

Code-Sharing:
We have to analyze the data we have gathered to show what is the most important factor to encourage people to participate in class or beyond more than active participation what is the one which can spur people to do better work in class. We assume there is more significant issue than grade motivating people in class. We plan to show how each student's work is improved based on various factors in class.

SketchUp:
In our next steps we want to investigate the three (four) big communities that have formed around SketchUp: the SketchUcation Forum, the Google SketchUp Help Group, the 3D Challenge Community, (and the Google SketchUp Competitions). We want to investigate the participation in these communities and explore the differences between the communities. Our next steps will be:
(1)Explore the degree of participation: We want to find a way to determine whether the participation in one group is higher than in another group. It would be nice if we were able to create a metric that is related to the degree of participation, for example, the average number of contributions per person per day might be an indicator, but it is problematic to gather all the data about all contributions within a community. This is why we consider to determine the degree of participation within a community in a more descriptive way, i.e. we want to look at the contributions and to evaluate the degree of participation based on what we see.
(2) Explore the differences between the communities: We want to look at the different technologies of the support system the communities use and to see how this affects the participation. Especially we want to see where differences in the degrees of participation can be derived from.
(3) See how members use and understand different technologies: We want to investigate what members use technologies like forums and repositories for. We also want to see how communities develop by finding new ways of using simple technologies like forums.
(4) Use communities and their differences to support or disprove our hypotheses: We want to use properties of the communities as indicators for the correctness of our hypotheses.

describe specific research emphasis of every member of your team

Jane: I have been working on researching existing story applications on Facebook and participating within the Story Gaps environment once we decided to analyze it. I have also been working on creating possible metrics for the next phase of data collection and analysis.

Mikel: I have been working with the Sketchup group to narrow down the areas we want to focus on. Specifically I have been working on the hypothesis that altruism does not exist in a collaborative design environment. I have been looking at the various usages of Sketchup and figuring out what "reward" each type of user hopes to get from contributing. I will be determining metrics that help us prove that "rewards" increase contributions in the Sketchup domain. I have also been working on methods of network visualization for the story telling team. We are hoping to create a diagram that connects contributors in a network according to certain metrics. Once the story telling team figures out what metrics are meant to be used, I will be helping in creating the network diagram to visualize the data.

Kyuhan: I have been working on updating the testing bed, researching possible motivation factors for class engagement, and gathering data for analyzing participant behavior.

Olga: I have been looking at communities that formed around SketchUp and technologies they use. First, I have been investigating what technologies that are provided by the 3D Warehouse are used, like sharing and collaboration on one single model, groups that are attached to a model or a collection, and collections themselves. Since these technologies (except for the categorization and management with collections) are very rarely used, I moved to investigate a technologies that are used outside the 3D Warehouse, such as forums, tutorials, wikis, blogs, etc. My further emphasis will be to find a way to determine the degree of participation within a community, either by creating a metric or by a more descriptive technique.

Walter: I spent some time getting familiar with the tools in the platforms. I'm now switching my focus to gathering and analyzing information that is available online. My main focus is collaboration through a competitive angle. Some key points are 1) what entices this type of competition and 2) how individuals (or groups) collaborate in and outside an organized competitive environment.

Jeff: I have largely spent time conducting literature and reference reviews to find theoretical content and practical examples of online motivation factors. This includes researching previous research on online motivation in general, community building, and factors to change levels of contributions. Research has spanned examples including social networks as well as scientific and youth communities. Theories on groups (i.e. TIP theory, McGrath) is also be evaluated to further connect many of the findings across the three projects.

George: I have also been experimenting with the Facebook application Story Gaps and other story apps. I have been brainstorming possible high-motivation Facebook apps that could yield a lot of useful data. I will help analyze data about the Story Gaps Facebook app. and visualize the data in a way that can emphasize the strength of relationships between contributors to the application. I have also helped Kyuhan gather and organize data about the game programs for the Code-Sharing project.

Antonio: I have worked on the technical perspective, mainly databases, of two branches of this project, (1) Code-Sharing: to create a normalized database using MySQL to store all the statistic data saved in files, (2) Storygaps: analyze and define the data on the storygaps.com web page to be able to "scrape" it and then save it in our local database. This two task are meant to facilitate the extraction of actual information from the existing data and also identify regular users.

References

E-DataViewer for Qualitative Coding of Electronic Data: http://www.cs.colorado.edu/~starbird/e-dataviewer.html

Bryant, Susan L., Andrea Forte, and Amy Bruckman. 2005. "Becoming Wikipedian: transformation of participation in a collaborative online encyclopedia." Pp. 1-10 in Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work. Sanibel Island, Florida, USA.

Gjoka, M., Sirivianos, M., Markopoulou, A., and Yang, X. 2008. Poking facebook: characterization of osn applications. In Proceedings of the First Workshop on online Social Networks (Seattle, WA, USA, August 18 - 18, 2008). WOSP '08. ACM, New York, NY, 31-36. DOI= http://doi.acm.org/10.1145/1397735.1397743

Joinson, Adam N. 2008. "Looking at, looking up or keeping up with people?: motives and use of facebook." Pp. 1027-1036 in Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems. Florence, Italy.

Walter, Sarah E., Karin Forssell, Brigid Barron, and Caitlin Martin. 2007. "Continuing motivation for game design." Pp. 2735-2740 in CHI '07 extended abstracts on Human factors in computing systems. San Jose, CA, USA.

Wang, Youcheng, and D. R. Fesenmaier. 2003. "Assessing Motivation of Contribution in Online Communities: An Empirical Investigation of an Online Travel Community." Electronic Markets 13:33.

list any specific problems you have encountered and need feedback/guidance on