Managing your informative networks

One of the main sources of "fresh information" in science is the email. More precisely, mailing lists. Depending on your area of expertise, you can find several email lists, where is possible to searching for:

• Interesting scientific discussions (like where can I find the first reference of algorithm X? is there a better way to do this? where is the best source of this topic?).
• Postdoctoral positions: jobs that you can take if you already got a PhD and you want to make a lot of moneynew exciting research for a short period (2 or 3 years).
• Special numbers of scientific journals: maybe the opportunity to publish a paper in a highly recognized journal in your area, or at least, getting a good feedback on your research.
• Conferences: the main source of getting information about new or classic conferences, specially the important dates and the list of interesting topics.

As a researcher between the fields of Information Retrieval and Machine Learning, I used to read the webir list for having the last news on the IR field. Unfortunately, Einat Amitay stop managing the list after 10 years of being there (the list is now closed). Recently, following the advice of my supervisor, I joined the list ML-news which seems to be a very active forum on the area of Machine Learning, but I am still looking for a substitute for webir... Any good suggestion for a mailing list in the field of IR?

On the other hand, what do you think of mailing lists? What lists do you belong to? Do you think email is very 90-ish? Do you trust more in facebook groups? Are you running a Machine Learning twitter account? Feel free to answer, please.