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Analysis of Zalando Customer Reviews
Learner III
Hey everyone
At my university we are using rapidminer in a big data class for text mining. For a project I wanted to analyse some bad and some good rated articles on the ecommerce site Zalando. The goal was to proove that bad rated articles have a significant higher amount of words like "does not fit", "darker than in the picture" etc.
For this purpose i crawled the webpages of 20 women shoes and downloaded their reviews. Now i made a data analysis and had a look at the occurence of the words in the review (see xml code).
What i can't manage to do right now is the cross reference those occurences with smaller sentences fragments like "too big" etc. Has anyone a clue how to do that or could point me into the right direction?
I am a total Newbie ;D , but i am planning on using rapidminer more and more in the future, because it really is a great too.
Thanks in advance.
Sarah
At my university we are using rapidminer in a big data class for text mining. For a project I wanted to analyse some bad and some good rated articles on the ecommerce site Zalando. The goal was to proove that bad rated articles have a significant higher amount of words like "does not fit", "darker than in the picture" etc.
For this purpose i crawled the webpages of 20 women shoes and downloaded their reviews. Now i made a data analysis and had a look at the occurence of the words in the review (see xml code).
What i can't manage to do right now is the cross reference those occurences with smaller sentences fragments like "too big" etc. Has anyone a clue how to do that or could point me into the right direction?
I am a total Newbie ;D , but i am planning on using rapidminer more and more in the future, because it really is a great too.
Thanks in advance.
Sarah
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="7.0.001">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="7.0.001" expanded="true" name="Process">
<parameter key="logverbosity" value="init"/>
<parameter key="random_seed" value="2001"/>
<parameter key="send_mail" value="never"/>
<parameter key="notification_email" value=""/>
<parameter key="process_duration_for_mail" value="30"/>
<parameter key="encoding" value="SYSTEM"/>
<process expanded="true">
<operator activated="true" class="text:process_document_from_file" compatibility="7.0.000" expanded="true" height="82" name="Process Documents from Files" width="90" x="45" y="34">
<list key="text_directories">
<parameter key="Gute Bewertungen" value="C:\Users\Sven\Dropbox\Big Data\AP2\Rapidminer\Files\Gute Reviews"/>
</list>
<parameter key="file_pattern" value="*"/>
<parameter key="extract_text_only" value="true"/>
<parameter key="use_file_extension_as_type" value="false"/>
<parameter key="content_type" value="txt"/>
<parameter key="encoding" value="SYSTEM"/>
<parameter key="create_word_vector" value="false"/>
<parameter key="vector_creation" value="TF-IDF"/>
<parameter key="add_meta_information" value="true"/>
<parameter key="keep_text" value="true"/>
<parameter key="prune_method" value="none"/>
<parameter key="prune_below_percent" value="3.0"/>
<parameter key="prune_above_percent" value="30.0"/>
<parameter key="prune_below_rank" value="0.05"/>
<parameter key="prune_above_rank" value="0.95"/>
<parameter key="datamanagement" value="double_sparse_array"/>
<process expanded="true">
<connect from_port="document" to_port="document 1"/>
<portSpacing port="source_document" spacing="0"/>
<portSpacing port="sink_document 1" spacing="0"/>
<portSpacing port="sink_document 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="remove_duplicates" compatibility="7.0.001" expanded="true" height="82" name="Remove Duplicates" width="90" x="246" y="34">
<parameter key="attribute_filter_type" value="subset"/>
<parameter key="attribute" value=""/>
<parameter key="attributes" value="text"/>
<parameter key="use_except_expression" value="false"/>
<parameter key="value_type" value="attribute_value"/>
<parameter key="use_value_type_exception" value="false"/>
<parameter key="except_value_type" value="time"/>
<parameter key="block_type" value="attribute_block"/>
<parameter key="use_block_type_exception" value="false"/>
<parameter key="except_block_type" value="value_matrix_row_start"/>
<parameter key="invert_selection" value="false"/>
<parameter key="include_special_attributes" value="true"/>
<parameter key="treat_missing_values_as_duplicates" value="false"/>
</operator>
<operator activated="true" class="set_role" compatibility="7.0.001" expanded="true" height="82" name="Set Role" width="90" x="380" y="34">
<parameter key="attribute_name" value="text"/>
<parameter key="target_role" value="regular"/>
<list key="set_additional_roles"/>
</operator>
<operator activated="true" class="text:process_document_from_data" compatibility="7.0.000" expanded="true" height="82" name="Process Documents from Data" width="90" x="514" y="34">
<parameter key="create_word_vector" value="true"/>
<parameter key="vector_creation" value="Term Occurrences"/>
<parameter key="add_meta_information" value="true"/>
<parameter key="keep_text" value="false"/>
<parameter key="prune_method" value="none"/>
<parameter key="prune_below_percent" value="3.0"/>
<parameter key="prune_above_percent" value="30.0"/>
<parameter key="prune_below_rank" value="0.05"/>
<parameter key="prune_above_rank" value="0.95"/>
<parameter key="datamanagement" value="double_sparse_array"/>
<parameter key="select_attributes_and_weights" value="false"/>
<list key="specify_weights"/>
<process expanded="true">
<operator activated="true" class="text:transform_cases" compatibility="7.0.000" expanded="true" height="68" name="Transform Cases" width="90" x="45" y="85">
<parameter key="transform_to" value="lower case"/>
</operator>
<operator activated="true" class="text:tokenize" compatibility="7.0.000" expanded="true" height="68" name="Tokenize" width="90" x="179" y="85">
<parameter key="mode" value="non letters"/>
<parameter key="characters" value=".:"/>
<parameter key="language" value="English"/>
<parameter key="max_token_length" value="3"/>
</operator>
<operator activated="true" class="text:stem_porter" compatibility="7.0.000" expanded="true" height="68" name="Stem (Porter)" width="90" x="313" y="85"/>
<operator activated="true" class="text:filter_stopwords_german" compatibility="7.0.000" expanded="true" height="68" name="Filter Stopwords (German)" width="90" x="447" y="85">
<parameter key="stop_word_list" value="Standard"/>
</operator>
<operator activated="true" class="text:filter_by_length" compatibility="7.0.000" expanded="true" height="68" name="Filter Tokens (by Length)" width="90" x="581" y="85">
<parameter key="min_chars" value="3"/>
<parameter key="max_chars" value="25"/>
</operator>
<connect from_port="document" to_op="Transform Cases" to_port="document"/>
<connect from_op="Transform Cases" from_port="document" to_op="Tokenize" to_port="document"/>
<connect from_op="Tokenize" from_port="document" to_op="Stem (Porter)" to_port="document"/>
<connect from_op="Stem (Porter)" from_port="document" to_op="Filter Stopwords (German)" to_port="document"/>
<connect from_op="Filter Stopwords (German)" from_port="document" to_op="Filter Tokens (by Length)" to_port="document"/>
<connect from_op="Filter Tokens (by Length)" from_port="document" to_port="document 1"/>
<portSpacing port="source_document" spacing="0"/>
<portSpacing port="sink_document 1" spacing="0"/>
<portSpacing port="sink_document 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="aggregate" compatibility="7.0.001" expanded="true" height="82" name="Aggregate" width="90" x="447" y="238">
<parameter key="use_default_aggregation" value="true"/>
<parameter key="attribute_filter_type" value="all"/>
<parameter key="attribute" value=""/>
<parameter key="attributes" value=""/>
<parameter key="use_except_expression" value="false"/>
<parameter key="value_type" value="attribute_value"/>
<parameter key="use_value_type_exception" value="false"/>
<parameter key="except_value_type" value="time"/>
<parameter key="block_type" value="attribute_block"/>
<parameter key="use_block_type_exception" value="false"/>
<parameter key="except_block_type" value="value_matrix_row_start"/>
<parameter key="invert_selection" value="false"/>
<parameter key="include_special_attributes" value="false"/>
<parameter key="default_aggregation_function" value="sum"/>
<list key="aggregation_attributes"/>
<parameter key="group_by_attributes" value=""/>
<parameter key="count_all_combinations" value="false"/>
<parameter key="only_distinct" value="false"/>
<parameter key="ignore_missings" value="true"/>
</operator>
<operator activated="true" class="transpose" compatibility="7.0.001" expanded="true" height="82" name="Transpose" width="90" x="581" y="187"/>
<connect from_port="input 1" to_op="Process Documents from Files" to_port="word list"/>
<connect from_op="Process Documents from Files" from_port="example set" to_op="Remove Duplicates" to_port="example set input"/>
<connect from_op="Remove Duplicates" from_port="example set output" to_op="Set Role" to_port="example set input"/>
<connect from_op="Set Role" from_port="example set output" to_op="Process Documents from Data" to_port="example set"/>
<connect from_op="Process Documents from Data" from_port="example set" to_op="Aggregate" to_port="example set input"/>
<connect from_op="Aggregate" from_port="example set output" to_op="Transpose" to_port="example set input"/>
<connect from_op="Transpose" from_port="example set output" to_port="result 1"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="source_input 2" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
<portSpacing port="sink_result 2" spacing="0"/>
</process>
</operator>
</process>
[ /code]
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