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Did anyone mention you on LinkedIn?

LinkedIn is continuing on rolling out a range of new features starting with mentions. Think of them like idly dropping someone or some organization into your interactions, a little like adding in a Twitter handle on Twitter.

This new feature hails towards making LinkedIn more interactive and engaging with your connections and the others that you interact with on your home page. This is a new feature but builds on the existing status message functionality (see this old blog post ) enabling you to flag someone’s name or organisation within the status message, comments or interaction on status messages that you share with your own network. A great way to build those relationships!

As soon as you start typing an individual or organisations name in your status it will pop up a pick list for you to choose from, see below

As soon as you mention someone in your status or that of others they will receive a notification (just like you get for interactions, messages and invites) so they are aware of it instantly, thus enabling them to continue the “conversation” within LinkedIn or outside of it over a telephone or coffee (my preference!).

Instructions for Mentions in LinkedIn Status Updates

1. From your status update box (top of your LinkedIn Homepage next to your photograph) just start typing the name of a connection or company you wish to mention in your status updateamongyour normal status message.

2. As soon as you start typing a name the drop-down box will appear with a list of connections / companies. Simply select the connection or company you wish to include in your comment or status update and that’s it!

3. After finishing your comment or status update, the mentioned company or person will receive a notification alerting them that they have been mentioned on LinkedIn. It’s as easy as that!

4. Note: You can even mention 2nd connections that already engaged in the comments section of posts on your LinkedIn homepage. This makes it nice and easy to start conversations with people who youaren’tconnected to using this functionality.

Despite the divorce of LinkedIn by Twitter back in July 2012 mentions will “translate” your mentions of individuals names on using the feature will automatically translate to their Twitter names within Twitter, very neat!

LinkedIn said in its release announcement of the mentions feature that there is more to come, rumours are rife and include a range of new potential functionality – be interesting to see what they release next.

My bet is on a positioning / GIS tie in, as it is weak in this area, what would you like to see in LinkedIn as the new feature?

4 thoughts on “ Did anyone mention you on LinkedIn?

Comments are closed.

LinkedIn seems to moving very speedily in the right direction here. It’s not a feature, but I’d like to see changes in the mobile app to enable more advanced functionality via mobiles.

Modifications to state are performed by creating and applying transactions. A client creates a transaction and submits it to the validator. The validator applies the transaction which causes a change to state.

Transactions are always wrapped inside of a batch. All transactions within a batch are committed to state together or not at all. Thus, batches are the atomic unit of state change.

The overall structure of batches and transactions includes Batch, BatchHeader, Transaction, and TransactionHeader:

Transaction Data Structure

Transactions are serialized using Protocol Buffers. They consists of two message types:

File: protos/transaction.proto

The Transaction header field is a serialized version of a TransactionHeader. The header is signed by the signer’s private key (not sent with the transaction) and the resulting signature is stored in header_signature. The header is present in the serialized form so that the exact bytes can be verified against the signature upon receipt of the Transaction.

The verification process verifies that the key in signer_public_key signed the header bytes resulting in header_signature.

The batcher_public_key field must match the public key used to sign the batch in which this transaction is contained.

The resulting serialized document is signed with the transactor’s private ECDSA key using the secp256k1 curve.

The validator expects a 64 byte “compact” signature. This is a concatenation of the R and S fields of the signature. Some libraries will include an additional header byte, recovery ID field, or provide DER encoded signatures. Sawtooth will reject the signature if it is anything other than 64 bytes.

Note

The original header bytes as constructed from the sender are used for verification of the signature. It is not considered good practice to de-serialize the header (for example, to a Python object) and then re-serialize the header with the intent to produce the same byte sequence as the original. Serialization can be sensitive to programming language or library, and any deviation would produce a sequence that would not match the signature; thus, best practice is to always use the original header bytes for verification.

Transaction Family

In Hyperledger Sawtooth, the set of possible transactions are defined by an extensible system called transaction families. Defining and implementing a new transaction family adds to the taxonomy of available transactions which can be applied. For example, in the language-specific tutorials that show you how to write your own transaction family (see the Application Developer’s Guide ), we define a transaction family called “xo” which defines a set of transactions for playing tic-tac-toe.

In addition to the name of the transaction family (family_name), each transaction specifies a family version string (family_version). The version string enables upgrading a transaction family while coordinating the nodes in the network to upgrade.

Dependencies and Input/Output Addresses

Transactions can depend upon other transactions, which is to say a dependent transaction cannot be applied prior to the transaction upon which it depends.

The dependencies field of a transaction allows explicitly specifying the transactions which must be applied prior to the current transaction. Explicit dependencies are useful in situations where transactions have dependencies but can not be placed in the same batch (for example, if the transactions are submitted at different times).

To assist in parallel scheduling operations, the inputs and outputs fields of a transaction contain state addresses. The scheduler determines the implicit dependencies between transactions based on interaction with state. The addresses may be fully qualified leaf-node addresses or partial prefix addresses. Input addresses are read from the state and output addresses are written to state. While they are specified by the client, input and output declarations on the transaction are enforced during transaction execution. Partial addresses work as wildcards and allow transactions to specify parts of the tree instead of just leaf nodes.

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The payload is used during transaction execution as a way to convey the change which should be applied to state. Only the transaction family processing the transaction will deserialize the payload; to all other components of the system, payload is just a sequence of bytes.

The payload_sha512 field contains a SHA-512 hash of the payload bytes. As part of the header, payload_sha512 is signed and later verified, while the payload field is not. To verify the payload field matches the header, a SHA-512 of the payload field can be compared to payload_sha512.

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The nonce field contains a random string generated by the client. With the nonce present, if two transactions otherwise contain the same fields, the nonce ensures they will generate different header signatures.

Batches are also serialized using Protocol Buffers. They consist of two message types:

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