Chapter 4: Data Collection and Derivation
4.3. Crowdsourcing and Crowdservicing
4.3.2. Supporting Secondary Case Study
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practice will focus on making connections and enabling connective collaboration between the content and participating agents on the platform to enable services and demand for services, or essentially facilitating the user-for-user, user-for-content and content-for-user relationships. Brian Chang adds that collective collaboration will occur as a part in the connective collaboration in order to “collect” collaboration efforts that can facilitate and bring resource to the connective collaboration practices.
4.3.2. Supporting Secondary Case Study
One of the recurring practical application comparison made between crowdsourcing and crowdservicing from the interview is the comparison between Yahoo! Answers and Quora. The interviewees have suggested that although both are free exchange question-and-answer platforms or “free knowledge exchange markets”
(Diener and Piller 2010) that support mass participation; they demonstrate different signature characteristics and results between crowdsourcing and crowdservicing. This case study will intend to assist in understanding the relationship between crowdsourcing and crowdservicing by demonstrate the different signature characteristics and results from Yahoo! Answers and Quora. The context of this secondary case study will focus on the techno-social process that the practical applications of crowdsourcing and crowdservicing have impacted upon, namely, cognition, communication, cooperation and collaboration. In addition, this secondary case study will attempt to draw a relationship between application of crowdsourcing and crowdservicing from the context of the Web’s developing and evolving phases.
4.3.2.1. Yahoo! Answers
Yahoo! Answers is a knowledge exchange markets that operates by application of crowdsourcing (Doan, Ramakrishnan et al. 2011). Essentially, it is a platform where a user asks a question and other users answer the question (Doan, Ramakrishnan et al. 2011). It is free platform that place emphasis on creating monetary values by bringing social and experience value to its users by allowing
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users to request and generate contents (Adamic, Zhang et al. 2008). The platform is open to users with a Yahoo! ID. The answering mechanism of Yahoo! Answers require the user to cite references but does not restrict or filter the answers based on the reference sources, i.e. the source can be disputable. The original questioners and the community then pick the best answer. Points are awarded for questions asked and answered, as well as for having one's answer selected as the top (Gomes 2006). It is worth noting that the answer provided by one user cannot be edited by another user. From Yahoo! Answers guideline and user instructions (Yahoo! 2013), to control the crowdsourcing practices and to prevent user-abuse in the crowdsourcing mechanisms, Yahoo! Answers utilize a points system that is weighted to encourage users to answer questions and to limit spam questions. This is also the mechanism for users to gain more site access on Yahoo! Answers. This mechanism provides a representation achievement that has no real world value, cannot be traded, and serve only as an indication of a user’s activeness on the platform. From the user guideline, Hierarchical statuses are also assigned based on the activeness of the user on the platform. In addition, Yahoo! forbids chatting activities between different users in the answers as published by the Yahoo!
Answers user guidelines. Figure 4.1 shows an example of the question-and-answer webpage of Yahoo! Answers. Figure 4.2 shows an example of a users’ information page provided by Yahoo! Answers.
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Figure 4.1.: An example of the Questions and Answers Webpage from Yahoo! Answers
Figure 4.2.: An example of a user’s information page on Yahoo! Answers
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positive impact on cognition. Its crowdsourcing mechanism collected a massive amount of answers shared by the users for the requested questions, but the answer quality decreases significantly as the amount of answer increase (Liu and Agichtein 2008). This implies that albeit Yahoo! Answers collect information, the information is “unfiltered” and may hinder the cognition process. Although this may be a crowdsourcing mechanism issue with Yahoo! Answers, many other knowledge market platform that collects “unfiltered” data suffer from this issue as well (Harper, Raban et al. 2008). Yahoo! Answers do however categorize the content that it receives and assign Tags to the each content that has been created. The cognition mechanisms in Yahoo! Answers strongly reflect Web 2.0’s description such that information is collected through user contribution and folksonomy.Yahoo! Answers has provided a channel for communication among its members.
From the user guideline (Yahoo! 2013), users on this platform can communicate with each other by Yahoo ID that may reveal the user’s contact information. This platform does not support communication beyond providing the contact information since interaction on the question and answer interface or webpage is prohibited. Yahoo! Answers have provided a channel that enables an indirect and sometimes ineffective many-to-many communication via voting by giving a positive point or negative point on an answer (Leibenluft 2007). This reflects the many-to-many communication characteristics of Web 2.0 albeit being indirect and at time ineffective.
Yahoo! Answers is a clear cooperative crowdsourcing practice from its initiatives of task distribution. It focuses on distributing the task for answering a question to its users raised by other users (Leibenluft 2007). Its mechanism can only choose the best answer from a set of user-generated answer even if the best answer is chosen from a list of problematic user-generated answers (Angwin 2008).
Since editing and commenting from other users is disabled, the problematic answers cannot be modified or corrected. Therefore, from this perspective, Yahoo! Answers diverge from the collaborative mindset of developing beyond the shared common
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goal of retrieving an answer; whereas the collaborative mindset would focus on retrieving an adequate or good answer. Since Yahoo! Answers is a cooperative crowdsourcing practice and there is no apparent sign of collaborative mechanisms, the relationship between Yahoo! Answers and collaboration is insignificant.
4.3.2.2. Quora
Quora is a knowledge exchange markets that operates under the application of crowdservicing as suggested by the interviewees. From another literature (Dawson and Bynghall 2012), although Quora is not explicitly cited as a practical application of crowdservicing, the notion of involving a crowd in creating and fulfilling a service is strongly emphasized. This reflects to the definition and description of crowdservicing that Davis has initially proposed (Davis 2011). It is built on an emphasis to improve upon and replace the existing problematic crowdsourcing knowledge exchange platforms (Lowman 2011). It is also a free platform that place emphasis on creating monetary values by bringing social and experience value to its users by allowing users to request and generate contents (Paul, Hong et al. 2012).
Quora is a knowledge exchange platform that supports content creation, editing, and organization by its user community (Kincaid 2010). Quora users can decide the ranking for the answers from a list of user-generated answer as well as suggest edits to existing answers provided by other users. Quora requires users to register with their real names rather than a digital ID. Quora also allows its users to connect their Quora accounts with their Twitter and Facebook accounts. Much like Twitter, Quora allows users to “follow” other users. In addition, Quora users can also create knowledge sharing blogs on any topic. There is no explicit recognition of activeness or achievement of a single on this platform other than providing a ranking of the answers from this user within a question-and-answers page as well as the amount of participation involved. Figure 4.3 shows an example question-and-answer page on Quora and Figure 4.4 shows an example of a user’s information page.
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Figure 4.3.: An example of the Questions and Answers Webpage from Quora
Figure 4.4.: An example of a user’s information page on Quora
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impact on cognition. Its crowdsourcing mechanism collected a massive amount of answers shared by the users for the requested questions. Not only so, through enabling editing and commenting Quora has enabled a possibility to connect the collected massive amount of answers (Paul, Hong et al. 2012). In other words, Quora has enabled the possibility for connective intelligence and a better collective intelligence (Paul, Hong et al. 2012). This implies that Quora collects “filtered”information, the information that as one of the interviewee, Carson Chen has suggested would enhance the cognition process. In addition, Quora categorize the content that it receives and assign Tags to the each content that has been created.
The cognition mechanism in Quora partly reflects with Web 2.0’s description such that information is collected through user contribution and folksonomy. Quora’s cognition mechanism also reflects with Web 3.0 description such that it connects information as well as with other platforms.
Quora has provided a channel for communication among its members. From the user interface, Quora allows its users to communicate with each other via a user’s information page. This platform not only supports communication by providing the contact information, it also supports a strong bonded many-to-many communication independent of space and time on the question-and-answer interface (Paul, Hong et al. 2012). Quora has provided a channel that enables a many-to-many communication. This strongly reflects the many-to-many communication characteristics of post Web 2.0 phases of the Web.
Part of Quora’s content generation is of cooperative nature; however, this cooperative nature is only a special case from the Quora’s collaborative practice.
Although Quora focuses on distributing the task for answering a question to its users raised by other users, it has enabled its users to collaborate closely by editing questions and suggesting edits to other users' answers (Wortham 2010). The cooperative scenario would only occur is the answer would meet the exact demand from the question. In most scenarios, the best answer would be a collaboration effort between the involved users. The users are connected to solve a question
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through Quora’s editing and commenting feedback mechanism then the collaboration efforts are collected and placed upon the platform (Paul, Hong et al.
2012). This feedback mechanism implies an iterative process of connecting users then collecting collaboration efforts (Paul, Hong et al. 2012). Thus, the final result will no-longer be just an answer; instead, the result from Quora would become a good answer that may bring more value to the users involved than the user and the platform would have anticipated, for example the monetary value for the platform and the social value of trust and reputation for the involved users (Paul, Hong et al.
2012). From this, Quora diverges from simple distribution of services, and converge more with concept of stakeholders providing services for each other when collaborating. Specifically, the question asker, in this case, the service requestor receives a good answer from the collected collaboration efforts and the question answers, in this case, the service providers receive social and experience values that would enable them to pursue for more values. From such analysis of the Quora’s collaboration mechanism, it is noted that the Quora’s collaboration mechanism resonant strongly with Web 2.5’s idea of using social interactions to build user interaction as well as the platform.
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