{
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  {
   "cell_type": "markdown",
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   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configuration\n",
    "\n",
    "*seed_words_filename:* The complete path to the input seed words list. For example: `path/to/seed_words/seed_words.txt`.\n",
    "\n",
    "*output_dir:* The path to the directory where you want to save the created annotation files. Please make sure to use a '/' (slash) in the end. For example: `path/to/output/`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "seed_words_filename = \"results/raw/seed_words.txt\"\n",
    "output_dir = \"results/annotated/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Directory Setup (Optional)\n",
    "Creates directories according to the configuration if not already created manually."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.exists(output_dir):\n",
    "    os.makedirs(output_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Seed Word Annotation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load seed words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(\"{}\".format(seed_words_filename), \"r\", encoding=\"utf-8\") as inputfile:\n",
    "    seed_words = [line.rstrip() for line in inputfile]\n",
    "print(\"loaded {} seed words\".format(len(seed_words)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create annotation file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"enter name of annotator: \")\n",
    "annotator = input()\n",
    "\n",
    "annotation_df = pd.DataFrame(index=seed_words, columns=[\"sentiment\"])\n",
    "annotation_df.index.name = \"word\"\n",
    "annotation_df.to_csv(\"{}{}_seed_words.csv\".format(output_dir, annotator.lower()))\n",
    "\n",
    "print(\"set up annotation file for: {}\".format(annotator))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Annotate seed words\n",
    "Please open the created annotation files (.csv files) with a spreadsheet program of your choice (e.g., Excel or LibreOffice Calc) and annotate the seed words.\n",
    "Make sure you use either of the following sentiment classes:\n",
    "\n",
    "* positive\n",
    "* negative\n",
    "* neutral\n",
    "\n",
    "Example:\n",
    "\n",
    "| word | sentiment |\n",
    "| --- | --- |\n",
    "| good | positive |\n",
    "| bad | negative |\n",
    "| house | neutral |\n",
    "\n",
    "Once you are finished, make sure to save the file using the **.csv** extension.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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