Enhance the site so that visitors can directly interact with it or among each other, enabling things like user-generated content, comments, voting, chat, or forms for data collection and interaction.

User Points User Picture

User Points User Picture awards points for adding a user picture to one's profile.

User Visits Advanced

The User Visits Advanced module is a contrib module for the User Visits module. It is extremely useful for social networking sites who wish to provide their users with statistics about the number of times a the users profile page is being viewed and by which other users. See the provided screen shot how the block of this module can look like.

This module comes with its own database table to store statistics per user profile (uid). At cron time, the data from the user_visits table is collected, aggregated and stored in the user_visits_adv table. It stores

  • the total number of visits per uid
  • the number of visits of the X past days per uid
  • the most recent visitors uids of the past Y hours

Installation

  • Enable the user_visits_adv module
  • Go to admin/user/user_visits and the advanced fieldset
  • You can choose to enable the two blocks: My recent visitors adv & My visitors history adv
  • Configure each block for the amount of data which should be handed over to the theming functions

Theming

The My visitors history adv block can be themed by overriding the following function
<?php
/**
* Theme function for history block
* @param $history is array with the views data of the past X days.

User-to-user Recommendation

IMPORTANT:This module is temporarily abandoned in favor of Browsing History Recommender module. Please refer to #509858: migrating to Browsing History Recommender. Future release of the module would take user relations from social networking modules and then make the user-to-user recommendation.

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The basic idea of this module is to automatically find similar users in the community, and then recommend new contents to users based on the fact that other similar users liked the contents. This is actually an implementation of collaborative filtering used in many recommender systems.

To calculate similarity among users, we now only adopts the user-comment relationship. That is, if two users made comments to the same nodes for several times, then we consider them quite similar to each other. This is especially useful for communities that have forums enabled. There might be other approaches that calculate similarities between users, but I haven't thought about it thoroughly. You are welcome to submit your ideas to the issue queue.

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