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A Dataset for Multi Target Stance Detection
... the multi-target stance dataset described earlier, where two stance labels are predicted for each ...each target, we use the average of the F1-scores (the harmonic mean of ... See full document
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Incorporating Label Dependencies in Multilabel Stance Detection
... multilabel stance detection in the context of three datasets: the Brexit Blog Corpus (BBC) (Simaki et ...each dataset where the utter- ances have been annotated with multiple ...possible ... See full document
5
Connecting targets to tweets : semantic attention based model for target specific stance detection
... the target information of each tweet was ignored, in order to measure each team’s overall performance, rather than performance on each separate ...given target and by mentioning other ...for ... See full document
16
A Topic-Aware Reinforced Model for Weakly Supervised Stance Detection
... given target, it usually talks about one or more target-related topics, and expresses attitudes towards these topics to implicitly stand its viewpoint towards the ...understanding target-related ... See full document
8
Cross Target Stance Classification with Self Attention Networks
... first dataset is from SemEval- 2016 Task 6 on Twitter stance detection, which contains stance-bearing tweets on different ...this dataset is only used for our qualitative ... See full document
6
Stance detection with bidirectional conditional encoding
... training dataset, pre- training of word embeddings is more helpful than random initialisation of ...and target vocabularies are shared, whereas Sep means they are ... See full document
11
Stance Detection in Code Mixed Hindi English Social Media Data using Multi Task Learning
... a stance; in favor, against or neutral towards a particular ...the stance taken by the individual became sig- nificantly important with the emergence in the usage of online social ...matic stance ... See full document
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A Joint Sentiment Target Stance Model for Stance Classification in Tweets
... joint stance and sentiment an- notated ...and stance and how the former can help detect the latter is an important research question that we address in this ...for stance detection in ...a ... See full document
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Stance Detection with Bidirectional Conditional Encoding
... In more detail, we train a word2vec model on a corpus of 395,212 unlabelled tweets, collected with the Twitter Keyword Search API 1 between Novem- ber 2015 and January 2016, plus all the tweets con- tained in the ... See full document
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Stance Detection with Bidirectional Conditional Encoding
... ber 2015 and January 2016, plus all the tweets con- tained in the official SemEval 2016 Stance Detec- tion datasets (Mohammad et al., 2016). The unla- belled tweets are collected so that they contain the targets ... See full document
10
Multi Task Stance Detection with Sentiment and Stance Lexicons
... The stance detection task aims to determine whether people are in favor of, against, or neu- tral towards a specific ...the target in stance detection might not be explicitly mentioned ... See full document
7
A Dataset for Detecting Stance in Tweets
... The Stance Dataset can be extended to more targets and do- mains using the same general methodology used to create ...the dataset and its extensions can be used in a number of applications such as ... See full document
8
Gradual Argumentation Evaluation for Stance Aggregation in Automated Fake News Detection
... A number of techniques have been employed for the purpose of building stance detection systems (Hanselowski et al., 2018), including Long-Short Term Memory networks (LSTMs) (Hanselowski et al., 2018; Shang ... See full document
11
Classifier Rank Identification using Multi Criteria Decision Making Method for Intrusion Detection Dataset
... In this work, KDD 99 dataset is applied as input to bayes net, naive bayes, NB updateable, random forest, oneR, zeroR, adaboostM1, decision stump, J48 and decision table classifiers. The performance of each ... See full document
7
Stance Detection in Facebook Posts of a German Right wing Party
... We propose the following model. The writer produces - under the assumption of truth com- mitment - some text. The reader, on the basis of shared (lexical) semantic knowledge, is able to identify what the text implies for ... See full document
10
Deep-Learning Based Real-Time Multiple-Object Detection and Tracking from Aerial Imagery via Flying Robot with GPU-based Embedded Devices
... Target detection has attracted significant attention for autonomous aerial vehicles due to its notable benefits and recent ...progress. Target tracking with an unmanned aerial vehicle (UAV) can be ... See full document
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Sarcasm Target Identification: Dataset and An Introductory Approach
... This target may be a subset of words in the text or a fall-back label ...first dataset which labels the target of ridicule in sarcastic tweets and book ...casm target, we present an ... See full document
8
Time-Delay-Based Multi-Target Detection and Power Delivering
... In order to show the performance of this method, the decomposition of reverse time operator (DORT) method in [8–14] is employed as a reference. Fig. 8 shows the energy concentration on the 4th target. Although the ... See full document
14
Simulation Analysis of Multi satellite Joint Detection Activity Target Capability
... seconds.The detection area is divided into 342 points by grid analysis method, and each point represents an area of about 800 square kilometers, because the area is divided according to the ...the detection ... See full document
7
A Multimodal Dataset for Deception Detection
... deceit detection has also considered the measurement and analysis of physiological responses such as heart rate, skin conductance, and body temperatures (Frank et ...the detection of criminal intent (Ewout ... See full document
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