def initialize_timestamp_array(comment_number, cascade_source_timestamp):
timestamp_column_names_list = ["timestamp_true", "timestamp"]
timestamp_array = np.empty((comment_number, 2), dtype=np.float64)
update_feature_value(timestamp_array, 0, 0, cascade_source_timestamp)
update_feature_value(timestamp_array, 0, 1, cascade_source_timestamp)
return timestamp_column_names_list, timestamp_array
def update_basic_max_depth_max_width_ratio(feature_array, i, j, intermediate_dict):
# comment_depth = intermediate_dict["comment_depth"]
# basic_max_depth_max_width_ratio = update_max_depth_max_width_ratio(intermediate_dict["depth_node_dict"],
# comment_depth,
# feature_to_list["basic_max_width"][-1])
basic_max_depth_max_width_ratio = update_max_depth_max_width_ratio(intermediate_dict["depth_node_dict"])
update_feature_value(feature_array, i, j, basic_max_depth_max_width_ratio)
def update_user_graph_hirsch_index(feature_array, i, j, intermediate_dict):
commenter_id = intermediate_dict["commenter_id"]
user_hirsch = update_user_hirsch_eponymous(
intermediate_dict["contributor_comment_count"], feature_array[i - 1,
j],
intermediate_dict["contributor_comment_count"][commenter_id])
update_feature_value(feature_array, i, j, user_hirsch)
def initialize_timestamp_array(comment_number,
cascade_source_timestamp):
timestamp_column_names_list = ["timestamp_true", "timestamp"]
timestamp_array = np.empty((comment_number, 2),
dtype=np.float64)
update_feature_value(timestamp_array, 0, 0, cascade_source_timestamp)
update_feature_value(timestamp_array, 0, 1, cascade_source_timestamp)
return timestamp_column_names_list, timestamp_array
def update_basic_max_depth_max_width_ratio(feature_array, i, j,
intermediate_dict):
# comment_depth = intermediate_dict["comment_depth"]
# basic_max_depth_max_width_ratio = update_max_depth_max_width_ratio(intermediate_dict["depth_node_dict"],
# comment_depth,
# feature_to_list["basic_max_width"][-1])
basic_max_depth_max_width_ratio = update_max_depth_max_width_ratio(
intermediate_dict["depth_node_dict"])
update_feature_value(feature_array, i, j, basic_max_depth_max_width_ratio)
def update_user_graph_indegree_normalized_entropy(feature_array, i, j,
intermediate_dict):
within_discussion_anonymous_coward = intermediate_dict[
"within_discussion_anonymous_coward"]
user_graph_indegree_normalized_entropy = update_normalized_graph_indegree_entropy(
intermediate_dict["contributor_replied_to_count"],
intermediate_dict["set_of_contributors"],
within_discussion_anonymous_coward)
update_feature_value(feature_array, i, j,
user_graph_indegree_normalized_entropy)
def update_user_graph_user_count_estimated(feature_array, i, j,
intermediate_dict):
user_count_estimated = update_user_count_estimated(
intermediate_dict["set_of_contributors"],
intermediate_dict["anonymous_coward_comments_counter"])
update_feature_value(feature_array, i, j, user_count_estimated)
def update_user_graph_randic_index(feature_array, i, j, intermediate_dict):
user_randic = update_randic_index(
intermediate_dict["user_randic_graph"].tocoo())
update_feature_value(feature_array, i, j, user_randic)
def update_user_graph_indegree_normalized_entropy(feature_array, i, j, intermediate_dict):
within_discussion_anonymous_coward = intermediate_dict["within_discussion_anonymous_coward"]
user_graph_indegree_normalized_entropy = update_normalized_graph_indegree_entropy(intermediate_dict["contributor_replied_to_count"],
intermediate_dict["set_of_contributors"],
within_discussion_anonymous_coward)
update_feature_value(feature_array, i, j, user_graph_indegree_normalized_entropy)
def update_branching_randic_index(feature_array, i, j, intermediate_dict):
branching_randic_index = update_randic_index(intermediate_dict["branching_randic_graph"].tocoo())
update_feature_value(feature_array, i, j, branching_randic_index)
def update_user_graph_hirsch_index(feature_array, i, j, intermediate_dict):
commenter_id = intermediate_dict["commenter_id"]
user_hirsch = update_user_hirsch_eponymous(intermediate_dict["contributor_comment_count"],
feature_array[i-1, j],
intermediate_dict["contributor_comment_count"][commenter_id])
update_feature_value(feature_array, i, j, user_hirsch)
def update_user_graph_outdegree_entropy(feature_array, i, j, intermediate_dict):
user_graph_outdegree_entropy = update_graph_outdegree_entropy(intermediate_dict["contributor_comment_count"])
update_feature_value(feature_array, i, j, user_graph_outdegree_entropy)
def initialize_handcrafted_features(comment_number,
handcrafted_feature_names_set,
op_is_anonymous):
"""
Initialize dictionary that maps a feature name to a score.
Output: - feature_to_list: Dictionary that maps feature names to scores.
"""
handcrafted_feature_names_list = list()
replicate_feature_if_anonymous_set = list()
handcrafted_function_list = list()
handcrafted_feature_array = np.empty((comment_number,
len(handcrafted_feature_names_set)),
dtype=np.float64)
####################################################################################################################
# Discussion tree basic features.
####################################################################################################################
if "basic_comment_count" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_comment_count")
handcrafted_function_list.append(getattr(basic_wrappers, "update_" + "basic_comment_count"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "basic_max_depth" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_max_depth")
handcrafted_function_list.append(getattr(basic_wrappers, "update_" + "basic_max_depth"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "basic_ave_depth" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_ave_depth")
handcrafted_function_list.append(getattr(basic_wrappers, "update_" + "basic_ave_depth"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "basic_max_width" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_max_width")
handcrafted_function_list.append(getattr(basic_wrappers, "update_" + "basic_max_width"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 1)
if "basic_ave_width" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_ave_width")
handcrafted_function_list.append(getattr(basic_wrappers, "update_" + "basic_ave_width"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 1)
if "basic_max_depth_max_width_ratio" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_max_depth_max_width_ratio")
handcrafted_function_list.append(getattr(basic_wrappers, "update_" + "basic_max_depth_max_width_ratio"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "basic_depth_width_ratio_ave" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_depth_width_ratio_ave")
handcrafted_function_list.append(getattr(basic_wrappers, "update_" + "basic_depth_width_ratio_ave"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
####################################################################################################################
# Discussion tree branching indices.
####################################################################################################################
if "branching_hirsch_index" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("branching_hirsch_index")
handcrafted_function_list.append(getattr(branching_wrappers, "update_" + "branching_hirsch_index"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "branching_wiener_index" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("branching_wiener_index")
handcrafted_function_list.append(getattr(branching_wrappers, "update_" + "branching_wiener_index"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "branching_randic_index" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("branching_randic_index")
handcrafted_function_list.append(getattr(branching_wrappers, "update_" + "branching_randic_index"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
####################################################################################################################
# User graph features
####################################################################################################################
if "user_graph_user_count" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_user_count")
replicate_feature_if_anonymous_set.append(len(handcrafted_function_list) - 1)
handcrafted_function_list.append(getattr(user_graph_wrappers, "update_" + "user_graph_user_count"))
if op_is_anonymous:
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
else:
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 1)
if "user_graph_user_count_estimated" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_user_count_estimated")
handcrafted_function_list.append(getattr(user_graph_wrappers, "update_" + "user_graph_user_count_estimated"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 1)
if "user_graph_hirsch_index" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_hirsch_index")
replicate_feature_if_anonymous_set.append(len(handcrafted_function_list) - 1)
handcrafted_function_list.append(getattr(user_graph_wrappers, "update_" + "user_graph_hirsch_index"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "user_graph_randic_index" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_randic_index")
replicate_feature_if_anonymous_set.append(len(handcrafted_function_list) - 1)
handcrafted_function_list.append(getattr(user_graph_wrappers, "update_" + "user_graph_randic_index"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "user_graph_outdegree_entropy" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_outdegree_entropy")
replicate_feature_if_anonymous_set.append(len(handcrafted_function_list) - 1)
handcrafted_function_list.append(getattr(user_graph_wrappers, "update_" + "user_graph_outdegree_entropy"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "user_graph_outdegree_normalized_entropy" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_outdegree_normalized_entropy")
replicate_feature_if_anonymous_set.append(len(handcrafted_function_list) - 1)
handcrafted_function_list.append(getattr(user_graph_wrappers, "update_" + "user_graph_outdegree_normalized_entropy"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 1)
if "user_graph_indegree_entropy" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_indegree_entropy")
replicate_feature_if_anonymous_set.append(len(handcrafted_function_list) - 1)
handcrafted_function_list.append(getattr(user_graph_wrappers, "update_" + "user_graph_indegree_entropy"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "user_graph_indegree_normalized_entropy" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_indegree_normalized_entropy")
replicate_feature_if_anonymous_set.append(len(handcrafted_function_list) - 1)
handcrafted_function_list.append(getattr(user_graph_wrappers, "update_" + "user_graph_indegree_normalized_entropy"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
####################################################################################################################
# Temporal features.
####################################################################################################################
if "temporal_first_half_mean_time" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("temporal_first_half_mean_time")
handcrafted_function_list.append(getattr(temporal_wrappers, "update_" + "temporal_first_half_mean_time"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "temporal_last_half_mean_time" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("temporal_last_half_mean_time")
handcrafted_function_list.append(getattr(temporal_wrappers, "update_" + "temporal_last_half_mean_time"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "temporal_std_time" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("temporal_std_time")
handcrafted_function_list.append(getattr(temporal_wrappers, "update_" + "temporal_std_time"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
if "temporal_timestamp_range" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("temporal_timestamp_range")
handcrafted_function_list.append(getattr(temporal_wrappers, "update_" + "temporal_timestamp_range"))
update_feature_value(handcrafted_feature_array, 0, len(handcrafted_function_list) - 1, 0)
return handcrafted_feature_names_list,\
replicate_feature_if_anonymous_set,\
handcrafted_function_list,\
handcrafted_feature_array
def update_branching_hirsch_index(feature_array, i, j, intermediate_dict):
comment_depth = intermediate_dict["comment_depth"]
branching_hirsch_index = update_hirsch_index(
intermediate_dict["depth_node_dict"], feature_array[i - 1, j],
comment_depth)
update_feature_value(feature_array, i, j, branching_hirsch_index)
def update_basic_comment_count(feature_array, i, j, intermediate_dict):
basic_comment_count = update_comment_count(feature_array[i-1, j] + 1)
update_feature_value(feature_array, i, j, basic_comment_count)
def initialize_handcrafted_features(comment_number,
handcrafted_feature_names_set,
op_is_anonymous):
"""
Initialize dictionary that maps a feature name to a score.
Output: - feature_to_list: Dictionary that maps feature names to scores.
"""
handcrafted_feature_names_list = list()
replicate_feature_if_anonymous_set = list()
handcrafted_function_list = list()
handcrafted_feature_array = np.empty(
(comment_number, len(handcrafted_feature_names_set)), dtype=np.float64)
####################################################################################################################
# Discussion tree basic features.
####################################################################################################################
if "basic_comment_count" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_comment_count")
handcrafted_function_list.append(
getattr(basic_wrappers, "update_" + "basic_comment_count"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "basic_max_depth" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_max_depth")
handcrafted_function_list.append(
getattr(basic_wrappers, "update_" + "basic_max_depth"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "basic_ave_depth" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_ave_depth")
handcrafted_function_list.append(
getattr(basic_wrappers, "update_" + "basic_ave_depth"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "basic_max_width" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_max_width")
handcrafted_function_list.append(
getattr(basic_wrappers, "update_" + "basic_max_width"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 1)
if "basic_ave_width" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_ave_width")
handcrafted_function_list.append(
getattr(basic_wrappers, "update_" + "basic_ave_width"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 1)
if "basic_max_depth_max_width_ratio" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append(
"basic_max_depth_max_width_ratio")
handcrafted_function_list.append(
getattr(basic_wrappers,
"update_" + "basic_max_depth_max_width_ratio"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "basic_depth_width_ratio_ave" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("basic_depth_width_ratio_ave")
handcrafted_function_list.append(
getattr(basic_wrappers, "update_" + "basic_depth_width_ratio_ave"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
####################################################################################################################
# Discussion tree branching indices.
####################################################################################################################
if "branching_hirsch_index" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("branching_hirsch_index")
handcrafted_function_list.append(
getattr(branching_wrappers, "update_" + "branching_hirsch_index"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "branching_wiener_index" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("branching_wiener_index")
handcrafted_function_list.append(
getattr(branching_wrappers, "update_" + "branching_wiener_index"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "branching_randic_index" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("branching_randic_index")
handcrafted_function_list.append(
getattr(branching_wrappers, "update_" + "branching_randic_index"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
####################################################################################################################
# User graph features
####################################################################################################################
if "user_graph_user_count" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_user_count")
replicate_feature_if_anonymous_set.append(
len(handcrafted_function_list) - 1)
handcrafted_function_list.append(
getattr(user_graph_wrappers, "update_" + "user_graph_user_count"))
if op_is_anonymous:
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
else:
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 1)
if "user_graph_user_count_estimated" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append(
"user_graph_user_count_estimated")
handcrafted_function_list.append(
getattr(user_graph_wrappers,
"update_" + "user_graph_user_count_estimated"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 1)
if "user_graph_hirsch_index" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_hirsch_index")
replicate_feature_if_anonymous_set.append(
len(handcrafted_function_list) - 1)
handcrafted_function_list.append(
getattr(user_graph_wrappers,
"update_" + "user_graph_hirsch_index"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "user_graph_randic_index" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_randic_index")
replicate_feature_if_anonymous_set.append(
len(handcrafted_function_list) - 1)
handcrafted_function_list.append(
getattr(user_graph_wrappers,
"update_" + "user_graph_randic_index"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "user_graph_outdegree_entropy" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_outdegree_entropy")
replicate_feature_if_anonymous_set.append(
len(handcrafted_function_list) - 1)
handcrafted_function_list.append(
getattr(user_graph_wrappers,
"update_" + "user_graph_outdegree_entropy"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "user_graph_outdegree_normalized_entropy" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append(
"user_graph_outdegree_normalized_entropy")
replicate_feature_if_anonymous_set.append(
len(handcrafted_function_list) - 1)
handcrafted_function_list.append(
getattr(user_graph_wrappers,
"update_" + "user_graph_outdegree_normalized_entropy"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 1)
if "user_graph_indegree_entropy" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("user_graph_indegree_entropy")
replicate_feature_if_anonymous_set.append(
len(handcrafted_function_list) - 1)
handcrafted_function_list.append(
getattr(user_graph_wrappers,
"update_" + "user_graph_indegree_entropy"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "user_graph_indegree_normalized_entropy" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append(
"user_graph_indegree_normalized_entropy")
replicate_feature_if_anonymous_set.append(
len(handcrafted_function_list) - 1)
handcrafted_function_list.append(
getattr(user_graph_wrappers,
"update_" + "user_graph_indegree_normalized_entropy"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
####################################################################################################################
# Temporal features.
####################################################################################################################
if "temporal_first_half_mean_time" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("temporal_first_half_mean_time")
handcrafted_function_list.append(
getattr(temporal_wrappers,
"update_" + "temporal_first_half_mean_time"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "temporal_last_half_mean_time" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("temporal_last_half_mean_time")
handcrafted_function_list.append(
getattr(temporal_wrappers,
"update_" + "temporal_last_half_mean_time"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "temporal_std_time" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("temporal_std_time")
handcrafted_function_list.append(
getattr(temporal_wrappers, "update_" + "temporal_std_time"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
if "temporal_timestamp_range" in handcrafted_feature_names_set:
handcrafted_feature_names_list.append("temporal_timestamp_range")
handcrafted_function_list.append(
getattr(temporal_wrappers, "update_" + "temporal_timestamp_range"))
update_feature_value(handcrafted_feature_array, 0,
len(handcrafted_function_list) - 1, 0)
return handcrafted_feature_names_list,\
replicate_feature_if_anonymous_set,\
handcrafted_function_list,\
handcrafted_feature_array
def update_basic_depth_width_ratio_ave(feature_array, i, j, intermediate_dict):
basic_depth_width_ratio_ave = update_depth_width_ratio_ave(intermediate_dict["depth_width_ratio_sum"],
intermediate_dict["depth_node_dict"])
update_feature_value(feature_array, i, j, basic_depth_width_ratio_ave)
def update_basic_max_depth(feature_array, i, j, intermediate_dict):
basic_max_depth = update_max_depth(intermediate_dict["depth_node_dict"])
update_feature_value(feature_array, i, j, basic_max_depth)
def update_basic_ave_width(feature_array, i, j, intermediate_dict):
basic_ave_width = update_ave_width(intermediate_dict["width_sum"],
intermediate_dict["depth_node_dict"])
update_feature_value(feature_array, i, j, basic_ave_width)
def update_basic_max_width(feature_array, i, j, intermediate_dict):
comment_depth = intermediate_dict["comment_depth"]
basic_max_width = update_max_width(intermediate_dict["depth_node_dict"],
comment_depth,
feature_array[i-1, j])
update_feature_value(feature_array, i, j, basic_max_width)
def update_basic_max_depth(feature_array, i, j, intermediate_dict):
basic_max_depth = update_max_depth(intermediate_dict["depth_node_dict"])
update_feature_value(feature_array, i, j, basic_max_depth)
def update_branching_randic_index(feature_array, i, j, intermediate_dict):
branching_randic_index = update_randic_index(
intermediate_dict["branching_randic_graph"].tocoo())
update_feature_value(feature_array, i, j, branching_randic_index)
def update_basic_ave_depth(feature_array, i, j, intermediate_dict):
basic_ave_depth = update_ave_depth(intermediate_dict["leaf_depth_sum"],
intermediate_dict["set_of_leaves"])
update_feature_value(feature_array, i, j, basic_ave_depth)
def update_user_graph_user_count_estimated(feature_array, i, j, intermediate_dict):
user_count_estimated = update_user_count_estimated(intermediate_dict["set_of_contributors"],
intermediate_dict["anonymous_coward_comments_counter"])
update_feature_value(feature_array, i, j, user_count_estimated)
def update_basic_max_width(feature_array, i, j, intermediate_dict):
comment_depth = intermediate_dict["comment_depth"]
basic_max_width = update_max_width(intermediate_dict["depth_node_dict"],
comment_depth, feature_array[i - 1, j])
update_feature_value(feature_array, i, j, basic_max_width)
def update_user_graph_randic_index(feature_array, i, j, intermediate_dict):
user_randic = update_randic_index(intermediate_dict["user_randic_graph"].tocoo())
update_feature_value(feature_array, i, j, user_randic)
def update_basic_ave_width(feature_array, i, j, intermediate_dict):
basic_ave_width = update_ave_width(intermediate_dict["width_sum"],
intermediate_dict["depth_node_dict"])
update_feature_value(feature_array, i, j, basic_ave_width)
def update_user_graph_indegree_entropy(feature_array, i, j, intermediate_dict):
user_graph_indegree_entropy = update_graph_indegree_entropy(intermediate_dict["contributor_replied_to_count"])
update_feature_value(feature_array, i, j, user_graph_indegree_entropy)
def update_user_graph_indegree_entropy(feature_array, i, j, intermediate_dict):
user_graph_indegree_entropy = update_graph_indegree_entropy(
intermediate_dict["contributor_replied_to_count"])
update_feature_value(feature_array, i, j, user_graph_indegree_entropy)
def update_branching_wiener_index(feature_array, i, j, intermediate_dict):
branching_wiener_index = update_wiener_index(intermediate_dict["subtree_size_vector"],
intermediate_dict["subtree_cum_size_vector"],
intermediate_dict["subtree_cum_size_sqrt_vector"])
update_feature_value(feature_array, i, j, branching_wiener_index)
def update_temporal_timestamp_range(feature_array, i, j, intermediate_dict):
timestamp_range = update_timestamp_range(intermediate_dict["initial_timestamp"],
intermediate_dict["latest_timestamp"])
update_feature_value(feature_array, i, j, timestamp_range)
def update_branching_hirsch_index(feature_array, i, j, intermediate_dict):
comment_depth = intermediate_dict["comment_depth"]
branching_hirsch_index = update_hirsch_index(intermediate_dict["depth_node_dict"],
feature_array[i-1, j],
comment_depth)
update_feature_value(feature_array, i, j, branching_hirsch_index)
def update_basic_comment_count(feature_array, i, j, intermediate_dict):
basic_comment_count = update_comment_count(feature_array[i - 1, j] + 1)
update_feature_value(feature_array, i, j, basic_comment_count)
def update_temporal_first_half_mean_time(feature_array, i, j, intermediate_dict):
temporal_first_half_mean_time = update_first_half_time_difference_mean(intermediate_dict["timestamp_differences"])
update_feature_value(feature_array, i, j, temporal_first_half_mean_time)
def update_branching_wiener_index(feature_array, i, j, intermediate_dict):
branching_wiener_index = update_wiener_index(
intermediate_dict["subtree_size_vector"],
intermediate_dict["subtree_cum_size_vector"],
intermediate_dict["subtree_cum_size_sqrt_vector"])
update_feature_value(feature_array, i, j, branching_wiener_index)
def update_user_graph_outdegree_entropy(feature_array, i, j,
intermediate_dict):
user_graph_outdegree_entropy = update_graph_outdegree_entropy(
intermediate_dict["contributor_comment_count"])
update_feature_value(feature_array, i, j, user_graph_outdegree_entropy)
def update_basic_ave_depth(feature_array, i, j, intermediate_dict):
basic_ave_depth = update_ave_depth(intermediate_dict["leaf_depth_sum"],
intermediate_dict["set_of_leaves"])
update_feature_value(feature_array, i, j, basic_ave_depth)
def update_basic_depth_width_ratio_ave(feature_array, i, j, intermediate_dict):
basic_depth_width_ratio_ave = update_depth_width_ratio_ave(
intermediate_dict["depth_width_ratio_sum"],
intermediate_dict["depth_node_dict"])
update_feature_value(feature_array, i, j, basic_depth_width_ratio_ave)
def update_temporal_std_time(feature_array, i, j, intermediate_dict):
time_difference_std = update_time_difference_std(intermediate_dict["timestamp_differences"])
update_feature_value(feature_array, i, j, time_difference_std)