5 Sessions of about 2-3 hours each.

Session 1: working with text
 Part 1 (2.5 hours)
  01A Vector Space Model - pre-processing, text similarity, tf.idf weighting (26 slides)
  01B Text Indexing and Search - inverted indices, encodings, precision/recall (27 slides)
 Part 2 (2 hours)
  02A Information Extraction - rule-based, wrapper induction, HMM for info extraction (34 slides)
  02B Text Summarization - multi-document summarization, update summarization (34 slides)

Session 2: text classification
 Part 1 (1.5 hours)
  03A Supervised Learning - basics, KNN, decision trees (29 slides)
  03B Text Classification - problems, practical aspects, evaluation (13 slides)
  03C Sentiment Analysis - polarity, lexical resources, practical aspects (17 slides)
 Part 2 (1.5 hours -- because students were familiar with the subject)
  03D Graph models - models, preferential attachment, evolving graphs, assortativity (46 slides)
  03E Link-based ranking - hits, PageRank, other centrality metrics (48 slides)

Session 3: working with graphs
 Part 1 (1.5 hour)
  04A Dense sub-graphs - sub-graphs, cuts, max-flow, shingling (69 slides)
 Part 2 (1 hour)
  04B Graph partitioning - projections, spectral methods (44 slides)
 Part 3 (1 hour)
  04C Social influence models - model, linear threshold, independent cascade (45 slides)

Session 4: social influence
 Part 1 (1.5 hours)
  04D Influence maximization - problem, greedy approximation (23 slides)
  05A Social media mining examples - economics, policits, health, crises (52 slides)
 Part 2 (1.5 hours)
  05B Natural experiments - randomized controlled experiments, Neyman's model (45 slides)
  05C Matching studies - matching and propensity matching design (51 slides)

Optional Sessions (if time allows)
  extra_A Clustering - partitional algorithms, 1D clustering (22 slides)
  extra_B K-means - and k-means++, k-means-- (31 slides)
  extra_C Hierarchical Clustering - algorithm, variants (33 slides)
  extra_D Link prediction
  extra E Link prediction and contents
  extra F Ethics of handling social data - privacy, discrimination, experimentation (46 slides)