Analyze Twitter User

No algorithm description given

0. TL;DR This is a recipe for Analyzing a Twitter User. It combines  diego/GetUserTweets ,  nlp/SocialSentimentAnalysis , and  nlp/LDA  into a micro-service. 1. Introduction Recipes are plug-n-play utilities that solve a specific problem in a novel way. These micro-services are comprised of one or more algorithms that allow users to quickly and easily get value from Algorithmia. They’re modular, and should be thought of as mini-products with obvious value. This recipe is composed in the following way: The recipe is given a twitter user and retrieves relevant tweets from twitter using  diego/GetUserTweets . These relevant tweets are analyzed, labelled and sorted by  nlp/SocialSentimentAnalysis . The top 20% (positive) tweets and the bottom 20% (negative) tweets are used to extract positive and negative topics using  nlp/LDA . The corresponding positive & negative topics as well as information about the user including followers and following. Input: (Required):   The twitter user to analyze (Required):   Twitter API authentication keys Output user twitter name number of followers number of people following A list of positive topics   (nlp/LDA output) A list of negative topics   (nlp/LDA output) 2. Query The query keyword/string:  The keyword that you're searching for on Twitter.   (key = "query") Example of a query keyword/string: {
 "query": "algorithmia"
} 3. Authentication Twitter API authentication keys:   The API keys that are necessary to access Twitter API service. You can get yours   here .   (key = "auth") {
 "auth": {
 "app_key": "xxxxxxx",
 "app_secret": "xxxxxxx",
 "oauth_token": "xxxxxxx",
 "oauth_token_secret": "xxxxxxx"
} 3. Example Example 1: Parameter 1: A twitter username Parameter 2: Twitter API authentication keys {
 "query": "doppenhe",
 "auth": {
 "app_key": "xxxxxxx",
 "app_secret": "xxxxxxx",
 "oauth_token": "xxxxxxx",
 "oauth_token_secret": "xxxxxxx"
} 4. Output Example 1: {     "following":302,    "is negative about":[        {           "obfuscated":1,          "algorithm":1,          "terrorists":1,          "humans":1,          "aims":1,          "computer":1,          "identify":1,          "time":2       }      ...      {           "code":2,          "machine-learning":1,          "scala":2,          "review":1,          "wtf":1,          "signs":1,          "make":1,          "died":1       }    ],    "followers":1390,    "screen_name":"doppenhe",    "is positive about":[        {           "binary":1,          "algorithmia":4,          "algorithm":2,          "show":1,          "support":1,          "doppenhe":1,          "advantage":1,          "today":3       }      ...    ] }

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1. Type your input

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3. Use this algorithm

curl -X POST -d '{{input | formatInput:"curl"}}' -H 'Content-Type: application/json' -H 'Authorization: Simple YOUR_API_KEY'
View cURL Docs
algo auth
algo run algo://diego/AnalyzeTwitterUser/0.1.6 -d '{{input | formatInput:"cli"}}'
View CLI Docs
import com.algorithmia.*;
import com.algorithmia.algo.*;

String input = "{{input | formatInput:"java"}}";
AlgorithmiaClient client = Algorithmia.client("YOUR_API_KEY");
Algorithm algo = client.algo("algo://diego/AnalyzeTwitterUser/0.1.6");
AlgoResponse result = algo.pipeJson(input);
View Java Docs
import com.algorithmia._
import com.algorithmia.algo._

val input = {{input | formatInput:"scala"}}
val client = Algorithmia.client("YOUR_API_KEY")
val algo = client.algo("algo://diego/AnalyzeTwitterUser/0.1.6")
val result = algo.pipeJson(input)
View Scala Docs
var input = {{input | formatInput:"javascript"}};
           .then(function(output) {
View Javascript Docs
var input = {{input | formatInput:"javascript"}};
           .then(function(response) {
View NodeJS Docs
import Algorithmia

input = {{input | formatInput:"python"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('diego/AnalyzeTwitterUser/0.1.6')
print algo.pipe(input)
View Python Docs

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("diego/AnalyzeTwitterUser/0.1.6")
result <- algo$pipe(input)$result
View R Docs
require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('diego/AnalyzeTwitterUser/0.1.6')
puts algo.pipe(input).result
View Ruby Docs
use algorithmia::*;

let input = {{input | formatInput:"rust"}};
let client = Algorithmia::client("YOUR_API_KEY");
let algo = client.algo('diego/AnalyzeTwitterUser/0.1.6');
let response = algo.pipe(input);
View Rust Docs
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