FakeNewsPerception#
- class pymovements.datasets.FakeNewsPerception(name: str = 'FakeNewsPerception', long_name: str = 'Fake News Perception Eye Tracking Corpus', mirrors: dict[str, Sequence[str]] = <factory>, resources: ResourceDefinitions = <factory>, experiment: Experiment = <factory>, extract: dict[str, bool] | None = None, custom_read_kwargs: dict[str, Any] = <factory>, column_map: dict[str, str] = <factory>, trial_columns: list[str] | None = None, time_column: str | None = None, time_unit: str | None = None, pixel_columns: list[str] | None = None, position_columns: list[str] | None = None, velocity_columns: list[str] | None = None, acceleration_columns: list[str] | None = None, distance_column: str | None = None, filename_format: dict[str, str] | None = None, filename_format_schema_overrides: dict[str, dict[str, type]] | None = None)[source]#
FakeNewsPerception dataset [Sümer et al., 2021].
FakeNewsPerception dataset consists of eye movements during reading, perceived believability scores, and questionnaires including Cognitive Reflection Test (CRT) and News-Find-Me (NFM) perception, collected from 25 participants with 60 news items. Eye movements are recorded to provide objective measures of information processing during news reading.
For more details see [Sümer et al., 2021].
- name#
The name of the dataset.
- Type:
str
- long_name#
The entire name of the dataset.
- Type:
str
- resources#
A list of dataset gaze_resources. Each list entry must be a dictionary with the following keys: - resource: The url suffix of the resource. This will be concatenated with the mirror. - filename: The filename under which the file is saved as. - md5: The MD5 checksum of the respective file.
- Type:
- experiment#
The experiment definition.
- Type:
- filename_format#
Regular expression which will be matched before trying to load the file. Namedgroups will appear in the fileinfo dataframe.
- Type:
dict[str, str] | None
- filename_format_schema_overrides#
If named groups are present in the filename_format, this makes it possible to cast specific named groups to a particular datatype.
- Type:
dict[str, dict[str, type]] | None
- column_map#
The keys are the columns to read, the values are the names to which they should be renamed.
- Type:
dict[str, str]
- custom_read_kwargs#
If specified, these keyword arguments will be passed to the file reading function.
- Type:
dict[str, Any]
Methods
__init__([name, long_name, mirrors, ...])from_yaml(path)Load a dataset definition from a YAML file.
to_dict(*[, exclude_private, exclude_none])Return dictionary representation.
to_yaml(path, *[, exclude_private, exclude_none])Save a dataset definition to a YAML file.
Attributes
acceleration_columnsdistance_columnextracthas_resourcesChecks for resources in
resources.pixel_columnsposition_columnstime_columntime_unittrial_columnsvelocity_columnsmirrors