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Sentiment Analysis : Facebook Status Messages

Sentiment Analysis : Facebook Status Messages. CS224N – Spring 2010 – Professor Manning Julia Kane Akhter ( kanej ) Steven Soria Jr . ( ssoriajr ). Goals. Compare and evaluate performance of MaxEnt , POS tagging, and Labeled LDA in semantic classification

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Sentiment Analysis : Facebook Status Messages

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  1. Sentiment Analysis:Facebook Status Messages CS224N – Spring 2010 – Professor Manning Julia Kane Akhter (kanej) Steven Soria Jr. (ssoriajr)

  2. Goals • Compare and evaluate performance of MaxEnt, POS tagging, and Labeled LDA in semantic classification • Assess whether a “best” binary classification model scales to more granular semantic labels • Appropriateness of Facebook data for semantic analysis

  3. Binary results “My work-husband’s last day”

  4. Multi-label results “Looks like I‘m waking up early next semester” HAPPY PLAYFUL SKEPTICAL UNHAPPY 1-Value (#N) 1.04 1.05 0.96 0.84 2-Value (#V) 0.03 0.24 0.10 0.53 3-Value (#A) 0.04 0.29 0.15 -0.03 4-Value (#E) -0.29 -0.12 -0.21 -0.27 5-SW-early_RB -0.12 -0.19 -0.19 0.50 5-SSHAPE-xx_xXX 0.32 -1.74 0.07 1.44 5-SW-next_JJ -0.19 0.17 0.37 -0.35 5-SSHAPE-xx_XX -0.03 -0.07 -0.22 0.29 5-SSHAPE-xxX_xXX 0.07 -0.37 -0.30 0.60 5-SW-semester_NN 0.07 -0.08 -0.05 0.07 5-SW-im_NN -0.36 -0.03 0.41 -0.02 5-SW-up_RB -0.04 -0.02 -0.14 0.19 5-SW-looks_VBZ 0.15 -0.01 -0.06 -0.08 5-SW-waking_VBG -0.07 -0.03 -0.01 0.11 5-SW-like_IN -0.24 -0.03 -0.12 0.39 Prob: 0.04 0.03 0.01 0.92

  5. Future Work • DATA • Hand-labeled data • Model actual distribution of labels as a prior • Pre-processing • SEMANTIC ANALYSIS • Subject of interest • Parser • FEATURE ENGINEERING • Classifier • LDA

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