Examples with TweetSerde cz.scholz.sentimentanalysis.model.TweetSerde used on opensource projects

Example 1 with TweetSerde

use of cz.scholz.sentimentanalysis.model.TweetSerde in project build-your-own-social-media-analytics-with-apache-kafka by scholzj.

the class TopologyProducer method buildTopology.

@Produces
public Topology buildTopology() {
    final TweetSerde tweetSerde = new TweetSerde();
    try {
        Criteria<String, Classifications> criteria = Criteria.builder().optApplication(Application.NLP.SENTIMENT_ANALYSIS).setTypes(String.class, Classifications.class).build();
        predictor = ModelZoo.loadModel(criteria).newPredictor();
    } catch (IOException | ModelNotFoundException | MalformedModelException e) {
        LOG.error("Failed to load model", e);
        throw new RuntimeException("Failed to load model", e);
    }
    final StreamsBuilder builder = new StreamsBuilder();
    builder.stream(SOURCE_TOPIC, Consumed.with(Serdes.ByteArray(), tweetSerde)).flatMapValues(value -> {
        if (value.getRetweetedStatus() != null) {
            // We ignore retweets => we do not want alert for every retweet
            return List.of();
        } else {
            String tweet = value.getText();
            try {
                Classifications classifications = predictor.predict(tweet);
                String statusUrl = "https://twitter.com/" + value.getUser().getScreenName() + "/status/" + value.getId();
                String alert = String.format("The following tweet was classified as %s with %2.2f%% probability: %s", classifications.best().getClassName().toLowerCase(Locale.ENGLISH), classifications.best().getProbability() * 100, statusUrl);
                // We care nly about strong results where probability is > 50%
                if (classifications.best().getProbability() > 0.50) {
                    LOG.infov("Tweeting: {0}", alert);
                    return List.of(alert);
                } else {
                    LOG.infov("Not tweeting: {0}", alert);
                    return List.of();
                }
            } catch (TranslateException e) {
                LOG.errorv("Failed to classify the tweet {0}", value);
                return List.of();
            }
        }
    }).peek((key, value) -> LOG.infov("{0}", value)).to(TARGET_TOPIC, Produced.with(Serdes.ByteArray(), Serdes.String()));
    return builder.build();
}