TL;DR: In this paper, a method for enabling users to exchange group electronic mail by establishing individual profiles and criteria, for determining personalized subsets within a group, is proposed, where users establish subscriptions to an electronic mailing list by specifying user profile data and acceptance criteria data to screen other users.
Abstract: A method for enabling users to exchange group electronic mail by establishing individual profiles and criteria, for determining personalized subsets within a group. Users establish subscriptions to an electronic mailing list by specifying user profile data and acceptance criteria data to screen other users. When a user subscribes, a web server establishes and stores an individualized recipient list including each matching subscriber and their degree of one-way or mutual match with the user. When the user then sends a message to the mailing list, an email server retrieves 100% her matches and then optionally filters her recipient list down to a message distribution list using each recipient's message criteria. The message is then distributed to matching users. Additionally, email archives and information contributions from users are stored in a database. A web server creates an individualized set of web pages for a user from the database, containing contributions only from users in his recipient list. In other embodiments, users apply one-way or mutual criteria matching and message profile criteria to other group forums, such as web-based discussion boards, chat, online clubs, USENET newsgroups, voicemail, instant messaging, web browsing side channel communities, and online gaming rendezvous.
TL;DR: In this paper, the authors introduce a comprehensive methodology for the selection of targets from a mailing list for direct mail, which is not based on an optimal selection strategy, whereas they explicitly take the profit function into account.
Abstract: Direct marketing mail is a growing area of marketing practice, yet the academic journals contain very little research on this topic. The most important issue for direct marketers is how to sample targets from a population for a direct mail campaign. Although some selection methods are described in the literature, there seems to be not a single paper discussing the analytical and statistical aspects involved. The objective of this paper is to introduce a comprehensive methodology for the selection of targets from a mailing list for direct mail. At least theoretically, this methodology leads to more efficient selection procedures than the existing ones. The latter are not based on an optimal selection strategy, whereas we explicitly take the profit function into account. By equating marginal costs and marginal returns we determine which households should receive a mailing in order to maximize expected profit. In the empirical part we show that our methodology has great predictive accuracy and generates higher net returns than traditional approaches.
TL;DR: In this paper, a method, apparatus, and system are directed towards seeding a user's contacts for their online social network, which is arranged to automatically recommend to the user a set of seed contacts that the user may employ to invite to join their social network.
Abstract: A method, apparatus, and system are directed towards seeding a user's contacts for their online social network. The invention is arranged to automatically recommend to the user a set of seed contacts that the user may employ to invite to join their social network. The set of seed contacts may be harvested from the user's existing portal activities, as well as other sources. In one embodiment, the invention analyzes portal activity, such as email exchanges with the user, and the like, to determine a frequency of contact with the user. Other sources may include but not be limited to emails, names within an address book of the user, names within an address book of another person, a buddy list, an instant messaging list, an activity, a mailing list, an online discussion group, a membership in a category, chat group, and the like.
TL;DR: Tests of decision aids indicate that they are superior to usual care interventions in improving knowledge and realistic expectations of the benefits and harms of options; reducing passivity in decision making; and lowering decisional conflict stemming from feeling uninformed.
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TL;DR: The findings indicate that strategic interaction has expanded knowledge sharing but with the caveat that extreme concentration of development could have an opposite effect.
Abstract: In stark contrast with the fully participative “bazaar” imagery of open source software (OSS) development, some recent empirical research has pointed out that much of the OSS development is carried out by a small percentage of developers. This raises serious concerns that concentration of development effort on a few will limit knowledge sharing and underutilize the available resources. Using the notion of strategic interaction, this paper argues that individual developers often interact strategically with other highly resourceful developers by forming a smaller but better organized structure to intensify the types of epistemic interactions that matter most to the OSS development. A general framework of strategic interaction including participation inequality, conversational interactivity, and cross-thread connectivity is proposed to examine its impact on knowledge sharing, and validated using 128 discussion threads from the K Desktop Environment (KDE) developer mailing list. The findings indicate that strategic interaction has expanded knowledge sharing but with the caveat that extreme concentration of development could have an opposite effect. For researchers, this study dovetails the incentive logic by proposing and validating the strategic aspects of OSS participation to better understand the collective dynamics underpinning OSS development. Practitioners can use this approach to evaluate and better support existing knowledge-sharing initiatives.