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It contains 4,077 tweets with overall 12,587 target entities, which 1,865 are positive, 4,707 are neutral and 6,015 are negative.\u003cbr\u003eThe annotation guidelines can be found in: http://www.dcs.warwick.ac.uk/~arkaitz/ukelection/guidelines.php\u003cbr\u003e- \"tweets\" contains original tweets and corresponding target entities and topics;- \"annotations\" contains annotation results and details about the process such as \"timespent\"; - \"tweets\" and \"annotations\" can be related and combined by tweet IDs;- \"train_id\" and \"test_id\" are the training and testing data split that is used for the experiments conducted in the paper below.\u003cbr\u003eMore information about this corpus can be found in our EACL paper, named \"\u003cb\u003eTDParse: Multi-target-specific sentiment recognition on Twitter\u003c/b\u003e\".\u003cbr\u003eLicense: The annotations are provided under a CC-BY license, while Twitter retains the ownership and rights of the content of the 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